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100+ Quantitative Research Topics For Students

Quantitative research is a research strategy focusing on quantified data collection and analysis processes. This research strategy emphasizes testing theories on various subjects. It also includes collecting and analyzing non-numerical data.

Quantitative research is a common approach in the natural and social sciences , like marketing, business, sociology, chemistry, biology, economics, and psychology. So, if you are fond of statistics and figures, a quantitative research title would be an excellent option for your research proposal or project.

How to Get a Title of Quantitative Research

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Finding a great title is the key to writing a great quantitative research proposal or paper. A title for quantitative research prepares you for success, failure, or mediocre grades. This post features examples of quantitative research titles for all students.

Putting together a research title and quantitative research design is not as easy as some students assume. So, an example topic of quantitative research can help you craft your own. However, even with the examples, you may need some guidelines for personalizing your research project or proposal topics.

So, here are some tips for getting a title for quantitative research:

Consider your area of studies
Look out for relevant subjects in the area
Expert advice may come in handy
Check out some sample quantitative research titles

Making a quantitative research title is easy if you know the qualities of a good title in quantitative research. Reading about how to make a quantitative research title may not help as much as looking at some samples. Looking at a quantitative research example title will give you an idea of where to start.

However, let’s look at some tips for how to make a quantitative research title:

The title should seem interesting to readers
Ensure that the title represents the content of the research paper
Reflect on the tone of the writing in the title
The title should contain important keywords in your chosen subject to help readers find your paper
The title should not be too lengthy
It should be grammatically correct and creative
It must generate curiosity

An excellent quantitative title should be clear, which implies that it should effectively explain the paper and what readers can expect. A research title for quantitative research is the gateway to your article or proposal. So, it should be well thought out. Additionally, it should give you room for extensive topic research.

A sample of quantitative research titles will give you an idea of what a good title for quantitative research looks like. Here are some examples:

What is the correlation between inflation rates and unemployment rates?
Has climate adaptation influenced the mitigation of funds allocation?
Job satisfaction and employee turnover: What is the link?
A look at the relationship between poor households and the development of entrepreneurship skills
Urbanization and economic growth: What is the link between these elements?
Does education achievement influence people’s economic status?
What is the impact of solar electricity on the wholesale energy market?
Debt accumulation and retirement: What is the relationship between these concepts?
Can people with psychiatric disorders develop independent living skills?
Children’s nutrition and its impact on cognitive development

Quantitative research applies to various subjects in the natural and social sciences. Therefore, depending on your intended subject, you have numerous options. Below are some good quantitative research topics for students:

The difference between the colorific intake of men and women in your country
Top strategies used to measure customer satisfaction and how they work
Black Friday sales: are they profitable?
The correlation between estimated target market and practical competitive risk assignment
Are smartphones making us brighter or dumber?
Nuclear families Vs. Joint families: Is there a difference?
What will society look like in the absence of organized religion?
A comparison between carbohydrate weight loss benefits and high carbohydrate diets?
How does emotional stability influence your overall well-being?
The extent of the impact of technology in the communications sector

Creativity is the key to creating a good research topic in quantitative research. Find a good quantitative research topic below:

How much exercise is good for lasting physical well-being?
A comparison of the nutritional therapy uses and contemporary medical approaches
Does sugar intake have a direct impact on diabetes diagnosis?
Education attainment: Does it influence crime rates in society?
Is there an actual link between obesity and cancer rates?
Do kids with siblings have better social skills than those without?
Computer games and their impact on the young generation
Has social media marketing taken over conventional marketing strategies?
The impact of technology development on human relationships and communication
What is the link between drug addiction and age?

Need more quantitative research title examples to inspire you? Here are some quantitative research title examples to look at:

Habitation fragmentation and biodiversity loss: What is the link?
Radiation has affected biodiversity: Assessing its effects
An assessment of the impact of the CORONA virus on global population growth
Is the pandemic truly over, or have human bodies built resistance against the virus?
The ozone hole and its impact on the environment
The greenhouse gas effect: What is it and how has it impacted the atmosphere
GMO crops: are they good or bad for your health?
Is there a direct link between education quality and job attainment?
How have education systems changed from traditional to modern times?
The good and bad impacts of technology on education qualities

Your examiner will give you excellent grades if you come up with a unique title and outstanding content. Here are some quantitative research examples titles.

Online classes: are they helpful or not?
What changes has the global CORONA pandemic had on the population growth curve?
Daily habits influenced by the global pandemic
An analysis of the impact of culture on people’s personalities
How has feminism influenced the education system’s approach to the girl child’s education?
Academic competition: what are its benefits and downsides for students?
Is there a link between education and student integrity?
An analysis of how the education sector can influence a country’s economy
An overview of the link between crime rates and concern for crime
Is there a link between education and obesity?

Research title example quantitative topics when well-thought guarantees a paper that is a good read. Look at the examples below to get started.

What are the impacts of online games on students?
Sex education in schools: how important is it?
Should schools be teaching about safe sex in their sex education classes?
The correlation between extreme parent interference on student academic performance
Is there a real link between academic marks and intelligence?
Teacher feedback: How necessary is it, and how does it help students?
An analysis of modern education systems and their impact on student performance
An overview of the link between academic performance/marks and intelligence
Are grading systems helpful or harmful to students?
What was the impact of the pandemic on students?

Irrespective of the course you take, here are some titles that can fit diverse subjects pretty well. Here are some creative quantitative research title ideas:

A look at the pre-corona and post-corona economy
How are conventional retail businesses fairing against eCommerce sites like Amazon and Shopify?
An evaluation of mortality rates of heart attacks
Effective treatments for cardiovascular issues and their prevention
A comparison of the effectiveness of home care and nursing home care
Strategies for managing effective dissemination of information to modern students
How does educational discrimination influence students’ futures?
The impacts of unfavorable classroom environment and bullying on students and teachers
An overview of the implementation of STEM education to K-12 students
How effective is digital learning?

If your paper addresses a problem, you must present facts that solve the question or tell more about the question. Here are examples of quantitative research titles that will inspire you.

An elaborate study of the influence of telemedicine in healthcare practices
How has scientific innovation influenced the defense or military system?
The link between technology and people’s mental health
Has social media helped create awareness or worsened people’s mental health?
How do engineers promote green technology?
How can engineers raise sustainability in building and structural infrastructures?
An analysis of how decision-making is dependent on someone’s sub-conscious
A comprehensive study of ADHD and its impact on students’ capabilities
The impact of racism on people’s mental health and overall wellbeing
How has the current surge in social activism helped shape people’s relationships?

Are you looking for an example of a quantitative research title? These ten examples below will get you started.

The prevalence of nonverbal communication in social control and people’s interactions
The impacts of stress on people’s behavior in society
A study of the connection between capital structures and corporate strategies
How do changes in credit ratings impact equality returns?
A quantitative analysis of the effect of bond rating changes on stock prices
The impact of semantics on web technology
An analysis of persuasion, propaganda, and marketing impact on individuals
The dominant-firm model: what is it, and how does it apply to your country’s retail sector?
The role of income inequality in economy growth
An examination of juvenile delinquents’ treatment in your country

Excellent Topics For Quantitative Research

Here are some titles for quantitative research you should consider:

Does studying mathematics help implement data safety for businesses
How are art-related subjects interdependent with mathematics?
How do eco-friendly practices in the hospitality industry influence tourism rates?
A deep insight into how people view eco-tourisms
Religion vs. hospitality: Details on their correlation
Has your country’s tourist sector revived after the pandemic?
How effective is non-verbal communication in conveying emotions?
Are there similarities between the English and French vocabulary?
How do politicians use persuasive language in political speeches?
The correlation between popular culture and translation

Here are some quantitative research titles examples for your consideration:

How do world leaders use language to change the emotional climate in their nations?
Extensive research on how linguistics cultivate political buzzwords
The impact of globalization on the global tourism sector
An analysis of the effects of the pandemic on the worldwide hospitality sector
The influence of social media platforms on people’s choice of tourism destinations
Educational tourism: What is it and what you should know about it
Why do college students experience math anxiety?
Is math anxiety a phenomenon?
A guide on effective ways to fight cultural bias in modern society
Creative ways to solve the overpopulation issue

An example of quantitative research topics for 12 th -grade students will come in handy if you want to score a good grade. Here are some of the best ones:

The link between global warming and climate change
What is the greenhouse gas impact on biodiversity and the atmosphere
Has the internet successfully influenced literacy rates in society
The value and downsides of competition for students
A comparison of the education system in first-world and third-world countries
The impact of alcohol addiction on the younger generation
How has social media influenced human relationships?
Has education helped boost feminism among men and women?
Are computers in classrooms beneficial or detrimental to students?
How has social media improved bullying rates among teenagers?

High school students can apply research titles on social issues or other elements, depending on the subject. Let’s look at some quantitative topics for students:

What is the right age to introduce sex education for students
Can extreme punishment help reduce alcohol consumption among teenagers?
Should the government increase the age of sexual consent?
The link between globalization and the local economy collapses
How are global companies influencing local economies?

There are numerous possible quantitative research topics you can write about. Here are some great quantitative research topics examples:

The correlation between video games and crime rates
Do college studies impact future job satisfaction?
What can the education sector do to encourage more college enrollment?
The impact of education on self-esteem
The relationship between income and occupation

You can find inspiration for your research topic from trending affairs on social media or in the news. Such topics will make your research enticing. Find a trending topic for quantitative research example from the list below:

How the country’s economy is fairing after the pandemic
An analysis of the riots by women in Iran and what the women gain to achieve
Is the current US government living up to the voter’s expectations?
How is the war in Ukraine affecting the global economy?
Can social media riots affect political decisions?

A proposal is a paper you write proposing the subject you would like to cover for your research and the research techniques you will apply. If the proposal is approved, it turns to your research topic. Here are some quantitative titles you should consider for your research proposal:

Military support and economic development: What is the impact in developing nations?
How does gun ownership influence crime rates in developed countries?
How can the US government reduce gun violence without influencing people’s rights?
What is the link between school prestige and academic standards?
Is there a scientific link between abortion and the definition of viability?

You can never have too many sample titles. The samples allow you to find a unique title you’re your research or proposal. Find a sample quantitative research title here:

Does weight loss indicate good or poor health?
Should schools do away with grading systems?
The impact of culture on student interactions and personalities
How can parents successfully protect their kids from the dangers of the internet?
Is the US education system better or worse than Europe’s?

If you’re a business major, then you must choose a research title quantitative about business. Let’s look at some research title examples quantitative in business:

Creating shareholder value in business: How important is it?
The changes in credit ratings and their impact on equity returns
The importance of data privacy laws in business operations
How do businesses benefit from e-waste and carbon footprint reduction?
Organizational culture in business: what is its importance?

We Are A Call Away

Interesting, creative, unique, and easy quantitative research topics allow you to explain your paper and make research easy. Therefore, you should not take choosing a research paper or proposal topic lightly. With your topic ready, reach out to us today for excellent research paper writing services .

Quantitative Research Examples

Updated October 9, 2023

Quantitative Research Examples – Introduction

Quantitative research is a systematic approach to collecting and analyzing data from various sources. It uses statistical, computational, and mathematical methods to extract valuable findings and draw conclusions. In this article, you will see different quantitative research examples, explaining how to collect and analyze data in quantitative research.

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7 Easy Quantitative Research Examples

Let us first see a few simple hypothetical quantitative research examples (Example #1 to Example #4).

Consider a researcher who conducted a quantitative survey among parents of children aged 1-8 years to study how many parents are fine with their children using phones. A total of 150 participated in the survey, where they rated their agreement on a 7-point scale.


Agreement Level	Strongly Disagree	Disagree	Slightly Disagree	Neutral	Slightly Agree	Agree	Strongly Agree

Method: To find the average perspective of parents on giving mobile phones to children, the researcher finds the average of all 150 collected values (Sum of all values ÷ 150).

Result : The results of the survey show the following insights:

The average rating was 4.6, indicating a tendency towards agreement regarding giving mobile phones to children.
20% of respondents “strongly agreed” (rated 7), 45% “agreed” (rated 6), and 17% “slightly agreed” (rated 5).
13% of respondents were “neutral” (rated 4).
Only 5% “slightly disagreed” (rated 3), and 0% “disagreed” or “strongly disagreed.”

We can see from the analyzed data that most parents are more likely to provide their children with mobile phones in today’s technological world.

Suppose a startup company, BVN corporation, wants to test their employee’s satisfaction levels. The company divides the employees into six groups of 5 employees each. They then conduct a survey asking the following questions where the answers must range from 1 (lowest) to 10 (highest).

Are you satisfied with the job?
What is your level of satisfaction with your work-life balance?
Would you recommend BVN corporation to other employees?
Once the employer gathers data from each employee in Group 1, they calculate the average rating for that group. They repeat this process for all the other groups.
Then, they determine the overall average for each aspect (like job satisfaction or work-life balance) by considering all the groups together.

Result: The following image depicts the rating given by groups and the overall average rating.

The interpretation of the results is as follows.

The average rating for job satisfaction among all groups is 7.0, meaning that employees are moderately satisfied with their jobs.
The average rating for work-life balance is 6.3. It means that employees are unsatisfied and the company needs some improvement.
The average rating for recommendations is 6.7. This score shows that employees have some good feelings towards the company. However, a company can improve its environment or culture to improve the recommendation ratings.

Let’s say a hospital performs quantitative research to analyze how efficient the hospital’s operations are. The hospital conducts a survey to collect data from both doctors and patients.

The survey included questions such as:

How much time does the doctor take for one patient? (Options: <10 mins, 10 to 30 mins, 30-50 mins, and 50+ mins).
How often does a patient come into the hospital? (1 time, 2-4 times, 4-8 times, and 8+ times)
Rate your (patient) satisfaction level (scale of 1 to 10).

Method: After getting all the information, the researcher determines the option that most people choose. For example, if 6 out of 10 people picked “<10 mins” for “How long the doctor spends with each patient?”, that’s what they consider as the average.

Result: The following are the key results from the survey.

The average time spent by a doctor for one patient varies from 10-30 mins.
The average number of patient visits per month is 3.
The average satisfaction of patients following doctor consultations is 7.

Let’s consider an NGO that wants to run an educational program in the village. Their aim is to improve the literacy rate in the village. However, before they launched the program, first, the organization first surveyed the entire village population (N=450) to know how many were likely to participate.

Result: In the survey, the NGO found that Individuals aged 30-45 showed 60% interest, while those below 30 years showed 45% interest, and those above 45 years showed 40% interest. Finally, 50% (225) of the village population participated in the program.

The four examples we just saw were simple hypothetical quantitative research examples. Now, let us see some real-life examples of quantitative research.

In 2015 , researchers conducted an experimental study on the effect of lack of sleep on colds. The study was a two-part experiment conducted on 164 healthy individuals. Participants had to record their one-week bedtime in the first part. In the second part, researchers quarantine the participants in a hotel and give them nose drops containing virus-causing colds, i.e., rhinovirus.

Data collection method: Participants recorded their bedtime, like sleeping and waking up time. Also, researchers used wrist actigraphy data to monitor sleep movement. Blood samples were collected to check the level (number) of rhinovirus antibodies. Tissues with mucus were used as a sign of illness, meaning if a participant used 10g or more tissues, they were sick. Method: The researchers used SPSS , a computer program, and logistic regression to predict which participants got colds and which didn’t. After that, they grouped the participants into categories based on how much they slept and, among those, how many people caught a cold.

Result: A few highlights from the study were as follows:

Of 164 participants, 124 received the virus, and only 48 among the 124 got sick.
Individuals who slept less than 5 hours during night-time were 4.5 times more likely to get sick.
Those who slept 5 -6 hours were 4.2 times more likely to get sick.
Participants who slept for 7+ hours had very low chances of catching a cold.

The image below shows the correlation between the total % of participants who got the cold and their respective sleeping hours.

In April 2020 , researchers conducted a cross-sectional survey in Bangladesh to explore the total sleep duration, night-time sleep, and daily naptime. 9,730 participants took a survey, including a questionnaire related to socio-demographic variables (age, gender, occupation), behavioral and health factors (smoking, alcohol consumption), depression, suicidal thoughts, night sleep duration, naptime duration, etc.

Data collection method: In this study, researchers collected the data through online survey forms from participants aged 18–64 in Bangladesh.

Analysis tools: SPSS 25.0, Stata 16, ArcGIS 10.7, etc.

Method: The researchers made digital maps of Bangladesh using GIS mapping. They divided the maps into different sections to show nap times, how long people slept at night, and the total sleep duration. They also made another map that revealed how areas with COVID-19 cases related to the amount of sleep people got at night in those places.

Result: Using the GIS maps, the researchers observed the following:

The study found that 64.7% slept for 7-9 hours at night, and the daily nap duration was 30-60 mins for 43.7% of participants.
Sleep duration was affected by unemployment, marital status, self-isolation, smoking cigarettes, social media use, financial difficulties, and depression.
Barisal region had 24% of participants with nap durations over 1 hour, and Rangpur had 67.60% with 7-9 hours of nightly sleep.

A study conducted in Kerman, Iran, in 2010-2011 , wanted to find the correlation between computer games and behavioral problems in adolescent boys. The study involved 384 male school students with a questionnaire and Achenbach’s Youth Self-Report (YSR) to assess their behavior problems. The YSR evaluates various issues, such as anxiety, depression, social problems, and more, comprising 10 categories.

Data collection method: The students filled out the questionnaire form regarding computer game usage, including how likely they were to play those games and if they contained any violent content.

Analysis tools: Bivariate regression, ANOVA, and SPSS 20.0.

Method: In the questionnaire, participants listed their top five favorite video games and rated their frequency of play, the level of violent content, and the presence of violent images on a 7-point scale. To calculate the exposure score, the researchers added the content and image scores and multiplied the result by the play frequency divided by 5.

In the YSR questionnaire, participants rated each game on a 5-point scale. To get dimension scores, the researchers totaled the scores for each item. Finally, they summed up the dimension scores to calculate the total score (all items combined).

Result: The study found that:

There is a 95% correlation between time spent on computer games and students’ depression/anxiety, social problems, aggressive behavior, and more.
Researchers observed that 17% showed aggressive behaviors, 12% had depression/anxiety, 9% had rule-breaking problems, and 6.4% had social issues.

Final Thoughts

Quantitative research examples rely on factual information, numerical data, and statistics. Its main advantage lies in the ease of predicting outcomes. Researchers gather information through different tools, equipment, surveys, questionnaires, quantified behaviors, and research methods, among other variables.

200+ Experimental Quantitative Research Topics For STEM Students In 2023

STEM stands for Science, Technology, Engineering, and Math, but these are not the only subjects we learn in school. STEM is like a treasure chest of skills that help students become great problem solvers, ready to tackle the real world’s challenges.

In this blog, we are here to explore the world of Research Topics for STEM Students. We will break down what STEM really means and why it is so important for students. In addition, we will give you the lowdown on how to pick a fascinating research topic. We will explain a list of 200+ Experimental Quantitative Research Topics For STEM Students.

And when it comes to writing a research title, we will guide you step by step. So, stay with us as we unlock the exciting world of STEM research – it is not just about grades; it is about growing smarter, more confident, and happier along the way.

What Is STEM?

Table of Contents

STEM is Science, Technology, Engineering, and Mathematics. It is a way of talking about things like learning, jobs, and activities related to these four important subjects. Science is about understanding the world around us, technology is about using tools and machines to solve problems, engineering is about designing and building things, and mathematics is about numbers and solving problems with them. STEM helps us explore, discover, and create cool stuff that makes our world better and more exciting.

Why STEM Research Is Important?

STEM research is important because it helps us learn new things about the world and solve problems. When scientists, engineers, and mathematicians study these subjects, they can discover cures for diseases, create new technology that makes life easier, and build things that help us live better. It is like a big puzzle where we put together pieces of knowledge to make our world safer, healthier, and more fun.

STEM research leads to new discoveries and solutions.
It helps find cures for diseases.
STEM technology makes life easier.
Engineers build things that improve our lives.
Mathematics helps us understand and solve complex problems.

How to Choose a Topic for STEM Research Paper

Here are some steps to choose a topic for STEM Research Paper:

Step 1: Identify Your Interests

Think about what you like and what excites you in science, technology, engineering, or math. It could be something you learned in school, saw in the news, or experienced in your daily life. Choosing a topic you’re passionate about makes the research process more enjoyable.

Step 2: Research Existing Topics

Look up different STEM research areas online, in books, or at your library. See what scientists and experts are studying. This can give you ideas and help you understand what’s already known in your chosen field.

Step 3: Consider Real-World Problems

Think about the problems you see around you. Are there issues in your community or the world that STEM can help solve? Choosing a topic that addresses a real-world problem can make your research impactful.

Step 4: Talk to Teachers and Mentors

Discuss your interests with your teachers, professors, or mentors. They can offer guidance and suggest topics that align with your skills and goals. They may also provide resources and support for your research.

Step 5: Narrow Down Your Topic

Once you have some ideas, narrow them down to a specific research question or project. Make sure it’s not too broad or too narrow. You want a topic that you can explore in depth within the scope of your research paper.

Here we will discuss 200+ Experimental Quantitative Research Topics For STEM Students:

Qualitative Research Topics for STEM Students:

Qualitative research focuses on exploring and understanding phenomena through non-numerical data and subjective experiences. Here are 10 qualitative research topics for STEM students:

Exploring the experiences of female STEM students in overcoming gender bias in academia.
Understanding the perceptions of teachers regarding the integration of technology in STEM education.
Investigating the motivations and challenges of STEM educators in underprivileged schools.
Exploring the attitudes and beliefs of parents towards STEM education for their children.
Analyzing the impact of collaborative learning on student engagement in STEM subjects.
Investigating the experiences of STEM professionals in bridging the gap between academia and industry.
Understanding the cultural factors influencing STEM career choices among minority students.
Exploring the role of mentorship in the career development of STEM graduates.
Analyzing the perceptions of students towards the ethics of emerging STEM technologies like AI and CRISPR.
Investigating the emotional well-being and stress levels of STEM students during their academic journey.

Easy Experimental Research Topics for STEM Students:

These experimental research topics are relatively straightforward and suitable for STEM students who are new to research:

Measuring the effect of different light wavelengths on plant growth.
Investigating the relationship between exercise and heart rate in various age groups.
Testing the effectiveness of different insulating materials in conserving heat.
Examining the impact of pH levels on the rate of chemical reactions.
Studying the behavior of magnets in different temperature conditions.
Investigating the effect of different concentrations of a substance on bacterial growth.
Testing the efficiency of various sunscreen brands in blocking UV radiation.
Measuring the impact of music genres on concentration and productivity.
Examining the correlation between the angle of a ramp and the speed of a rolling object.
Investigating the relationship between the number of blades on a wind turbine and energy output.

Research Topics for STEM Students in the Philippines:

These research topics are tailored for STEM students in the Philippines:

Assessing the impact of climate change on the biodiversity of coral reefs in the Philippines.
Studying the potential of indigenous plants in the Philippines for medicinal purposes.
Investigating the feasibility of harnessing renewable energy sources like solar and wind in rural Filipino communities.
Analyzing the water quality and pollution levels in major rivers and lakes in the Philippines.
Exploring sustainable agricultural practices for small-scale farmers in the Philippines.
Assessing the prevalence and impact of dengue fever outbreaks in urban areas of the Philippines.
Investigating the challenges and opportunities of STEM education in remote Filipino islands.
Studying the impact of typhoons and natural disasters on infrastructure resilience in the Philippines.
Analyzing the genetic diversity of endemic species in the Philippine rainforests.
Assessing the effectiveness of disaster preparedness programs in Philippine communities.

Frontend Project Ideas
Business Intelligence Projects For Beginners

Good Research Topics for STEM Students:

These research topics are considered good because they offer interesting avenues for investigation and learning:

Developing a low-cost and efficient water purification system for rural communities.
Investigating the potential use of CRISPR-Cas9 for gene therapy in genetic disorders.
Studying the applications of blockchain technology in securing medical records.
Analyzing the impact of 3D printing on customized prosthetics for amputees.
Exploring the use of artificial intelligence in predicting and preventing forest fires.
Investigating the effects of microplastic pollution on aquatic ecosystems.
Analyzing the use of drones in monitoring and managing agricultural crops.
Studying the potential of quantum computing in solving complex optimization problems.
Investigating the development of biodegradable materials for sustainable packaging.
Exploring the ethical implications of gene editing in humans.

Unique Research Topics for STEM Students:

Unique research topics can provide STEM students with the opportunity to explore unconventional and innovative ideas. Here are 10 unique research topics for STEM students:

Investigating the use of bioluminescent organisms for sustainable lighting solutions.
Studying the potential of using spider silk proteins for advanced materials in engineering.
Exploring the application of quantum entanglement for secure communication in the field of cryptography.
Analyzing the feasibility of harnessing geothermal energy from underwater volcanoes.
Investigating the use of CRISPR-Cas12 for rapid and cost-effective disease diagnostics.
Studying the interaction between artificial intelligence and human creativity in art and music generation.
Exploring the development of edible packaging materials to reduce plastic waste.
Investigating the impact of microgravity on cellular behavior and tissue regeneration in space.
Analyzing the potential of using sound waves to detect and combat invasive species in aquatic ecosystems.
Studying the use of biotechnology in reviving extinct species, such as the woolly mammoth.

Experimental Research Topics for STEM Students in the Philippines

Research topics for STEM students in the Philippines can address specific regional challenges and opportunities. Here are 10 experimental research topics for STEM students in the Philippines:

Assessing the effectiveness of locally sourced materials for disaster-resilient housing construction in typhoon-prone areas.
Investigating the utilization of indigenous plants for natural remedies in Filipino traditional medicine.
Studying the impact of volcanic soil on crop growth and agriculture in volcanic regions of the Philippines.
Analyzing the water quality and purification methods in remote island communities.
Exploring the feasibility of using bamboo as a sustainable construction material in the Philippines.
Investigating the potential of using solar stills for freshwater production in water-scarce regions.
Studying the effects of climate change on the migration patterns of bird species in the Philippines.
Analyzing the growth and sustainability of coral reefs in marine protected areas.
Investigating the utilization of coconut waste for biofuel production.
Studying the biodiversity and conservation efforts in the Tubbataha Reefs Natural Park.

Capstone Research Topics for STEM Students in the Philippines:

Capstone research projects are often more comprehensive and can address real-world issues. Here are 10 capstone research topics for STEM students in the Philippines:

Designing a low-cost and sustainable sanitation system for informal settlements in urban Manila.
Developing a mobile app for monitoring and reporting natural disasters in the Philippines.
Assessing the impact of climate change on the availability and quality of drinking water in Philippine cities.
Designing an efficient traffic management system to address congestion in major Filipino cities.
Analyzing the health implications of air pollution in densely populated urban areas of the Philippines.
Developing a renewable energy microgrid for off-grid communities in the archipelago.
Assessing the feasibility of using unmanned aerial vehicles (drones) for agricultural monitoring in rural Philippines.
Designing a low-cost and sustainable aquaponics system for urban agriculture.
Investigating the potential of vertical farming to address food security in densely populated urban areas.
Developing a disaster-resilient housing prototype suitable for typhoon-prone regions.

Experimental Quantitative Research Topics for STEM Students:

Experimental quantitative research involves the collection and analysis of numerical data to conclude. Here are 10 Experimental Quantitative Research Topics For STEM Students interested in experimental quantitative research:

Examining the impact of different fertilizers on crop yield in agriculture.
Investigating the relationship between exercise and heart rate among different age groups.
Analyzing the effect of varying light intensities on photosynthesis in plants.
Studying the efficiency of various insulation materials in reducing building heat loss.
Investigating the relationship between pH levels and the rate of corrosion in metals.
Analyzing the impact of different concentrations of pollutants on aquatic ecosystems.
Examining the effectiveness of different antibiotics on bacterial growth.
Trying to figure out how temperature affects how thick liquids are.
Finding out if there is a link between the amount of pollution in the air and lung illnesses in cities.
Analyzing the efficiency of solar panels in converting sunlight into electricity under varying conditions.

Descriptive Research Topics for STEM Students

Descriptive research aims to provide a detailed account or description of a phenomenon. Here are 10 topics for STEM students interested in descriptive research:

Describing the physical characteristics and behavior of a newly discovered species of marine life.
Documenting the geological features and formations of a particular region.
Creating a detailed inventory of plant species in a specific ecosystem.
Describing the properties and behavior of a new synthetic polymer.
Documenting the daily weather patterns and climate trends in a particular area.
Providing a comprehensive analysis of the energy consumption patterns in a city.
Describing the structural components and functions of a newly developed medical device.
Documenting the characteristics and usage of traditional construction materials in a region.
Providing a detailed account of the microbiome in a specific environmental niche.
Describing the life cycle and behavior of a rare insect species.

Research Topics for STEM Students in the Pandemic:

The COVID-19 pandemic has raised many research opportunities for STEM students. Here are 10 research topics related to pandemics:

Analyzing the effectiveness of various personal protective equipment (PPE) in preventing the spread of respiratory viruses.
Studying the impact of lockdown measures on air quality and pollution levels in urban areas.
Investigating the psychological effects of quarantine and social isolation on mental health.
Analyzing the genomic variation of the SARS-CoV-2 virus and its implications for vaccine development.
Studying the efficacy of different disinfection methods on various surfaces.
Investigating the role of contact tracing apps in tracking & controlling the spread of infectious diseases.
Analyzing the economic impact of the pandemic on different industries and sectors.
Studying the effectiveness of remote learning in STEM education during lockdowns.
Investigating the social disparities in healthcare access during a pandemic.
Analyzing the ethical considerations surrounding vaccine distribution and prioritization.

Research Topics for STEM Students Middle School

Research topics for middle school STEM students should be engaging and suitable for their age group. Here are 10 research topics:

Investigating the growth patterns of different types of mold on various food items.
Studying the negative effects of music on plant growth and development.
Analyzing the relationship between the shape of a paper airplane and its flight distance.
Investigating the properties of different materials in making effective insulators for hot and cold beverages.
Studying the effect of salt on the buoyancy of different objects in water.
Analyzing the behavior of magnets when exposed to different temperatures.
Investigating the factors that affect the rate of ice melting in different environments.
Studying the impact of color on the absorption of heat by various surfaces.
Analyzing the growth of crystals in different types of solutions.
Investigating the effectiveness of different natural repellents against common pests like mosquitoes.

Technology Research Topics for STEM Students

Technology is at the forefront of STEM fields. Here are 10 research topics for STEM students interested in technology:

Developing and optimizing algorithms for autonomous drone navigation in complex environments.
Exploring the use of blockchain technology for enhancing the security and transparency of supply chains.
Investigating the applications of virtual reality (VR) and augmented reality (AR) in medical training and surgery simulations.
Studying the potential of 3D printing for creating personalized prosthetics and orthopedic implants.
Analyzing the ethical and privacy implications of facial recognition technology in public spaces.
Investigating the development of quantum computing algorithms for solving complex optimization problems.
Explaining the use of machine learning and AI in predicting and mitigating the impact of natural disasters.
Studying the advancement of brain-computer interfaces for assisting individuals with
disabilities.
Analyzing the role of wearable technology in monitoring and improving personal health and wellness.
Investigating the use of robotics in disaster response and search and rescue operations.

Scientific Research Topics for STEM Students

Scientific research encompasses a wide range of topics. Here are 10 research topics for STEM students focusing on scientific exploration:

Investigating the behavior of subatomic particles in high-energy particle accelerators.
Studying the ecological impact of invasive species on native ecosystems.
Analyzing the genetics of antibiotic resistance in bacteria and its implications for healthcare.
Exploring the physics of gravitational waves and their detection through advanced interferometry.
Investigating the neurobiology of memory formation and retention in the human brain.
Studying the biodiversity and adaptation of extremophiles in harsh environments.
Analyzing the chemistry of deep-sea hydrothermal vents and their potential for life beyond Earth.
Exploring the properties of superconductors and their applications in technology.
Investigating the mechanisms of stem cell differentiation for regenerative medicine.
Studying the dynamics of climate change and its impact on global ecosystems.

Interesting Research Topics for STEM Students:

Engaging and intriguing research topics can foster a passion for STEM. Here are 10 interesting research topics for STEM students:

Exploring the science behind the formation of auroras and their cultural significance.
Investigating the mysteries of dark matter and dark energy in the universe.
Studying the psychology of decision-making in high-pressure situations, such as sports or
emergencies.
Analyzing the impact of social media on interpersonal relationships and mental health.
Exploring the potential for using genetic modification to create disease-resistant crops.
Investigating the cognitive processes involved in solving complex puzzles and riddles.
Studying the history and evolution of cryptography and encryption methods.
Analyzing the physics of time travel and its theoretical possibilities.
Exploring the role of Artificial Intelligence in creating art and music.
Investigating the science of happiness and well-being, including factors contributing to life satisfaction.

Practical Research Topics for STEM Students

Practical research often leads to real-world solutions. Here are 10 practical research topics for STEM students:

Developing an affordable and sustainable water purification system for rural communities.
Designing a low-cost, energy-efficient home heating and cooling system.
Investigating strategies for reducing food waste in the supply chain and households.
Studying the effectiveness of eco-friendly pest control methods in agriculture.
Analyzing the impact of renewable energy integration on the stability of power grids.
Developing a smartphone app for early detection of common medical conditions.
Investigating the feasibility of vertical farming for urban food production.
Designing a system for recycling and upcycling electronic waste.
Studying the environmental benefits of green roofs and their potential for urban heat island mitigation.
Analyzing the efficiency of alternative transportation methods in reducing carbon emissions.

Experimental Research Topics for STEM Students About Plants

Plants offer a rich field for experimental research. Here are 10 experimental research topics about plants for STEM students:

Investigating the effect of different light wavelengths on plant growth and photosynthesis.
Studying the impact of various fertilizers and nutrient solutions on crop yield.
Analyzing the response of plants to different types and concentrations of plant hormones.
Investigating the role of mycorrhizal in enhancing nutrient uptake in plants.
Studying the effects of drought stress and water scarcity on plant physiology and adaptation mechanisms.
Analyzing the influence of soil pH on plant nutrient availability and growth.
Investigating the chemical signaling and defense mechanisms of plants against herbivores.
Studying the impact of environmental pollutants on plant health and genetic diversity.
Analyzing the role of plant secondary metabolites in pharmaceutical and agricultural applications.
Investigating the interactions between plants and beneficial microorganisms in the rhizosphere.

Qualitative Research Topics for STEM Students in the Philippines

Qualitative research in the Philippines can address local issues and cultural contexts. Here are 10 qualitative research topics for STEM students in the Philippines:

Exploring indigenous knowledge and practices in sustainable agriculture in Filipino communities.
Studying the perceptions and experiences of Filipino fishermen in coping with climate change impacts.
Analyzing the cultural significance and traditional uses of medicinal plants in indigenous Filipino communities.
Investigating the barriers and facilitators of STEM education access in remote Philippine islands.
Exploring the role of traditional Filipino architecture in natural disaster resilience.
Studying the impact of indigenous farming methods on soil conservation and fertility.
Analyzing the cultural and environmental significance of mangroves in coastal Filipino regions.
Investigating the knowledge and practices of Filipino healers in treating common ailments.
Exploring the cultural heritage and conservation efforts of the Ifugao rice terraces.
Studying the perceptions and practices of Filipino communities in preserving marine biodiversity.

Science Research Topics for STEM Students

Science offers a diverse range of research avenues. Here are 10 science research topics for STEM students:

Investigating the potential of gene editing techniques like CRISPR-Cas9 in curing genetic diseases.
Studying the ecological impacts of species reintroduction programs on local ecosystems.
Analyzing the effects of microplastic pollution on aquatic food webs and ecosystems.
Investigating the link between air pollution and respiratory health in urban populations.
Studying the role of epigenetics in the inheritance of acquired traits in organisms.
Analyzing the physiology and adaptations of extremophiles in extreme environments on Earth.
Investigating the genetics of longevity and factors influencing human lifespan.
Studying the behavioral ecology and communication strategies of social insects.
Analyzing the effects of deforestation on global climate patterns and biodiversity loss.
Investigating the potential of synthetic biology in creating bioengineered organisms for beneficial applications.

Correlational Research Topics for STEM Students

Correlational research focuses on relationships between variables. Here are 10 correlational research topics for STEM students:

Analyzing the correlation between dietary habits and the incidence of chronic diseases.
Studying the relationship between exercise frequency and mental health outcomes.
Investigating the correlation between socioeconomic status and access to quality healthcare.
Analyzing the link between social media usage and self-esteem in adolescents.
Studying the correlation between academic performance and sleep duration among students.
Investigating the relationship between environmental factors and the prevalence of allergies.
Analyzing the correlation between technology use and attention span in children.
Studying how environmental factors are related to the frequency of allergies.
Investigating the link between parental involvement in education and student achievement.
Analyzing the correlation between temperature fluctuations and wildlife migration patterns.

Quantitative Research Topics for STEM Students in the Philippines

Quantitative research in the Philippines can address specific regional issues. Here are 10 quantitative research topics for STEM students in the Philippines

Analyzing the impact of typhoons on coastal erosion rates in the Philippines.
Studying the quantitative effects of land use change on watershed hydrology in Filipino regions.
Investigating the quantitative relationship between deforestation and habitat loss for endangered species.
Analyzing the quantitative patterns of marine biodiversity in Philippine coral reef ecosystems.
Studying the quantitative assessment of water quality in major Philippine rivers and lakes.
Investigating the quantitative analysis of renewable energy potential in specific Philippine provinces.
Analyzing the quantitative impacts of agricultural practices on soil health and fertility.
Studying the quantitative effectiveness of mangrove restoration in coastal protection in the Philippines.
Investigating the quantitative evaluation of indigenous agricultural practices for sustainability.
Analyzing the quantitative patterns of air pollution and its health impacts in urban Filipino areas.

Things That Must Keep In Mind While Writing Quantitative Research Title

Here are a few things that must be kept in mind while writing a quantitative research:

1. Be Clear and Precise

Make sure your research title is clear and says exactly what your study is about. People should easily understand the topic and goals of your research by reading the title.

2. Use Important Words

Include words that are crucial to your research, like the main subjects, who you’re studying, and how you’re doing your research. This helps others find your work and understand what it’s about.

3. Avoid Confusing Words

Stay away from words that might confuse people. Your title should be easy to grasp, even if someone isn’t an expert in your field.

4. Show Your Research Approach

Tell readers what kind of research you did, like experiments or surveys. This gives them a hint about how you conducted your study.

5. Match Your Title with Your Research Questions

Make sure your title matches the questions you’re trying to answer in your research. It should give a sneak peek into what your study is all about and keep you on the right track as you work on it.

STEM students, addressing what STEM is and why research matters in this field. It offered an extensive list of research topics , including experimental, qualitative, and regional options, catering to various academic levels and interests. Whether you’re a middle school student or pursuing advanced studies, these topics offer a wealth of ideas. The key takeaway is to choose a topic that resonates with your passion and aligns with your goals, ensuring a successful journey in STEM research. Choose the best Experimental Quantitative Research Topics For Stem Students today!

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Quantitative Research: Examples of Research Questions and Solutions

Are you ready to embark on a journey into the world of quantitative research? Whether you’re a seasoned researcher or just beginning your academic journey, understanding how to formulate effective research questions is essential for conducting meaningful studies. In this blog post, we’ll explore examples of quantitative research questions across various disciplines and discuss how StatsCamp.org courses can provide the tools and support you need to overcome any challenges you may encounter along the way.

Understanding Quantitative Research Questions

Quantitative research involves collecting and analyzing numerical data to answer research questions and test hypotheses. These questions typically seek to understand the relationships between variables, predict outcomes, or compare groups. Let’s explore some examples of quantitative research questions across different fields:

Examples of quantitative research questions

What is the relationship between class size and student academic performance?
Does the use of technology in the classroom improve learning outcomes?
How does parental involvement affect student achievement?
What is the effect of a new drug treatment on reducing blood pressure?
Is there a correlation between physical activity levels and the risk of cardiovascular disease?
How does socioeconomic status influence access to healthcare services?
What factors influence consumer purchasing behavior?
Is there a relationship between advertising expenditure and sales revenue?
How do demographic variables affect brand loyalty?

Stats Camp: Your Solution to Mastering Quantitative Research Methodologies

At StatsCamp.org, we understand that navigating the complexities of quantitative research can be daunting. That’s why we offer a range of courses designed to equip you with the knowledge and skills you need to excel in your research endeavors. Whether you’re interested in learning about regression analysis, experimental design, or structural equation modeling, our experienced instructors are here to guide you every step of the way.

Bringing Your Own Data

One of the unique features of StatsCamp.org is the opportunity to bring your own data to the learning process. Our instructors provide personalized guidance and support to help you analyze your data effectively and overcome any roadblocks you may encounter. Whether you’re struggling with data cleaning, model specification, or interpretation of results, our team is here to help you succeed.

Courses Offered at StatsCamp.org

Latent Profile Analysis Course : Learn how to identify subgroups, or profiles, within a heterogeneous population based on patterns of responses to multiple observed variables.
Bayesian Statistics Course : A comprehensive introduction to Bayesian data analysis, a powerful statistical approach for inference and decision-making. Through a series of engaging lectures and hands-on exercises, participants will learn how to apply Bayesian methods to a wide range of research questions and data types.
Structural Equation Modeling (SEM) Course : Dive into advanced statistical techniques for modeling complex relationships among variables.
Multilevel Modeling Course : A in-depth exploration of this advanced statistical technique, designed to analyze data with nested structures or hierarchies. Whether you’re studying individuals within groups, schools within districts, or any other nested data structure, multilevel modeling provides the tools to account for the dependencies inherent in such data.

As you embark on your journey into quantitative research, remember that StatsCamp.org is here to support you every step of the way. Whether you’re formulating research questions, analyzing data, or interpreting results, our courses provide the knowledge and expertise you need to succeed. Join us today and unlock the power of quantitative research!

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98 Quantitative Research Questions & Examples

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As researchers, we know how powerful quantitative research data can be in helping answer strategic questions. Here, I’ve detailed 23 use cases and curated 98 quantitative market research questions with examples – making this a post you should add to your bookmark list , so you can quickly refer back.

I’ve formatted this post to show you 10-15 questions for each use case. At the end of each section, I also share a quicker way to get similar insights using modern market research tools like Similarweb.

What is a quantitative research question?

Quantitative market research questions tell you the what, how, when, and where of a subject. From trendspotting to identifying patterns or establishing averages– using quantitative data is a clear and effective way to start solving business problems.

Types of quantitative research questions

Quantitative market research questions are divided into two main types: descriptive and causal.

Descriptive research questions seek to quantify a phenomenon by focusing on a certain population or phenomenon to measure certain aspects of it, such as frequency, average, or relationship.
Causal research questions explore the cause-and-effect relationship between two or more variables.

The ultimate list of questions for quantitative market research

Get clear explanations of the different applications and approaches to quantitative research–with the added bonus of seeing what questions to ask and how they can impact your business.

Examples of quantitative research questions for competitive analysis

A powerful example of quantitative research in play is when it’s used to inform a competitive analysis . A process that’s used to analyze and understand how industry leaders and companies of interest are performing.

Pro Tip: Collect data systematically, and use a competitive analysis framework to record your findings. You can refer back to it when you repeat the process later in the year.

What is the market share of our major competitors?
What is the average purchase price of our competitors’ products?
How often do our competitors release new products?
What is the total number of customer reviews for our competitors’ products?
What is the average rating of our competitors’ products?
What is the average customer satisfaction score for our competitors?
What is the average return rate of our competitors’ products?
What is the average shipping time for our competitors’ products?
What is the average price discount offered by our competitors?
What is the average lifespan of our competitors’ products?

With this data, you can determine your position in the market and benchmark your performance against rival companies. It can then be used to improve offerings, service standards, pricing, positioning, and operational effectiveness. Notice that all questions can be answered with a numerical response , a key component of all successful examples of quantitative market research questions.

Quantitative research question example: market analysis

‍♀️ Question: What is the market share of our major competitors?

Insight sought: Industry market share of leaders and key competitors.

Challenges with traditional quantitative research methods: Outdated data is a major consideration; data freshness remains critical, yet is often tricky to obtain using traditional research methods. Markets shift fast, so being able to obtain and track market share in real time is a challenge many face.

A new approach: Similarweb enables you to track this key business KPI in real-time using digital data directly from the platform. On any day, you can see what your market share is, along with any players in your market. Plus, you get to see rising stars showing significant growth, who may pose a threat through market disruption or new tactics.

⏰ Time to insight: 30 seconds

✅ How it’s done: Using Similarweb’s Web Industry Analysis, two digital metrics give you the intel needed to decipher the market share in any industry. I’m using the Banking, Credit, and Lending market throughout these examples. I’ve selected the US market, analyzing the performance of the previous 3 months.

Share of visits

Here, I can see the top players in my market based on the number of unique visitors to their sites. On top of the raw data that shows me the volume of visitors as a figure, I can quickly see the two players ( Capital One and Chase ) that have grown and by what percentage. On the side, you can see rising players in the industry. Now, while my initial question was to establish the market share of my major competitors, I can see there are a few disruptive players in my market who I’d want to track too; Synchrony.com being one of particular interest, given their substantial growth and traffic numbers.

Share of search

quantitative market research question example

Viewing the overall market size based on total search volumes, you can explore industry leaders in more detail. The top websites are the top five players, ranking by traffic share . You can also view the month-over-month change in visits, which shows you who is performing best at any given time . It’s the same five names, with Paypal and Chase leading the pack. However, I see Wells Fargo is better at attracting repeat visitors, while Capital One and Bank of America perform better at drawing in unique visitors.

In answer to my question, what is the market share of my major competitors, I can quickly use Similarweb’s quantitative data to get my answer.

Traffic distribution breakdown with Similarweb

This traffic share visual can be downloaded from the platform. It plots the ten industry leader’s market share and allocates the remaining share to the rest of the market.

I can also download a market quadrant analysis, which takes two key data points, traffic share and unique visitors, and plots the industry leaders. All supporting raw data can be downloaded in .xls format or connected to other business intelligence platforms via the API.

Quantitative research questions for consumer behavior studies

These studies measure and analyze consumer behavior , preferences, and habits . Any type of audience analysis helps companies better understand customer intent, and adjust offerings, messaging, campaigns, SEO, and ultimately offer more relevant products and services within a market.

What is the average amount consumers spend on a certain product each month?
What percentage of consumers are likely to purchase a product based on its price?
How do the demographics of the target audience affect their purchasing behavior?
What type of incentive is most likely to increase the likelihood of purchase?
How does the store’s location impact product sales and turnover?
What are the key drivers of product loyalty among consumers?
What are the most commonly cited reasons for not buying a product?
How does the availability of product information impact purchasing decisions?
What is the average time consumers spend researching a product before buying it?
How often do consumers use social media when making a purchase decision?

While applying a qualitative approach to such studies is also possible, it’s a great example of quantitative market research in action. For larger corporations, studies that involve a large, relevant sample size of a target market deliver vital consumer insights at scale .

Read More: 83 Qualitative Research Questions & Examples

Quantitative research question and answer: content strategy and analysis

‍♀️ Question: What type of content performed best in the market this past month?

Insight sought: Establish high-performing campaigns and promotions in a market.

Challenges with traditional quantitative research methods: Whether you consider putting together a panel yourself, or paying a company to do it for you, quantitative research at scale is costly and time-consuming. What’s more, you have to ensure that sampling is done right and represents your target audience.

A new approach: Data analysis is the foundation of our entire business. For over 10 years, Similarweb has developed a unique , multi-dimensional approach to understanding the digital world. To see the specific campaigns that resonate most with a target audience, use Similarweb’s Popular Pages feature. Key metrics show which campaigns achieve the best results for any site (including rival firms), campaign take-up, and periodic changes in performance and interest.

✅ How it’s done: I’ve chosen Capital One and Wells Fargo to review. Using the Popular Pages campaign filter, I can view all pages identified by a URL parameter UTM. For clarity, I’ve highlighted specific campaigns showing high-growth and increasing popularity. I can view any site’s trending, new, or best-performing pages using a different filter.

In this example, I have highlighted three campaigns showing healthy growth, covering teen checking accounts, performance savings accounts, and add-cash-in-store. Next, I will perform the same check for another key competitor in my market.

Wells Fargo popular pages extract Similarweb

Here, I can see financial health tools campaigns with over 300% month-over-month growth and smarter credit and FICO campaigns showing strong performance. This tells me that campaigns focussing on education and tools are growing in popularity within this market.

Examples of quantitative research questions for brand tracking

These studies are designed to measure customers’ awareness, perceptions, behaviors, and attitudes toward a brand over time. Different applications include measuring brand awareness , brand equity, customer satisfaction, and purchase or usage intent.

These types of research surveys ask questions about brand knowledge, brand attributes, brand perceptions, and brand loyalty . The data collected can then be used to understand the current state of a brand’s performance, identify improvements, and track the success of marketing initiatives.

To what extent is Brand Z associated with innovation?
How do consumers rate the quality of Brand Z’s products and services?
How has the awareness of Brand Z changed over the past 6 months?
How does Brand Z compare to its competitors in terms of customer satisfaction?
To what extent do consumers trust Brand Z?
How likely are consumers to recommend Brand Z?
What factors influence consumers’ purchase decisions when considering Brand Z?
What is the average customer satisfaction score for equity?
How does equity’s customer service compare to its competitors?
How do customer perceptions of equity’s brand values compare to its competitors?

Quantitative research question example and answer: brand tracking

‍♀️ Question: How has the awareness of Brand Z changed over the past 6 months?

Insight sought: How has brand awareness changed for my business and competitors over time.

⏰ Time to insight: 2 minutes

✅ How it’s done: Using Similarweb’s search overview, I can quickly identify which brands in my chosen market have the highest brand awareness over any time period or location. I can view these stats as a custom market or examine brands individually.

Here, I’ve chosen a custom view that shows me five companies side-by-side. In the top right-hand corner, under branded traffic, you get a quick snapshot of the share of website visits that were generated by branded keywords. A branded keyword is when a consumer types the brand name + a search term.

Below that, you will see the search traffic and engagement section. Here, I’ve filtered the results to show me branded traffic as a percentage of total traffic. Similarweb shows me how branded search volumes grow or decline monthly. Helping me answer the question of how brand awareness has changed over time.

Quantitative research questions for consumer ad testing

Another example of using quantitative research to impact change and improve results is ad testing. It measures the effectiveness of different advertising campaigns. It’s often known as A/B testing , where different visuals, content, calls-to-action, and design elements are experimented with to see which works best. It can show the impact of different ads on engagement and conversions.

A range of quantitative market research questions can be asked and analyzed to determine the optimal approach.

How does changing the ad’s headline affect the number of people who click on the ad?
How does varying the ad’s design affect its click-through rate?
How does altering the ad’s call-to-action affect the number of conversions?
How does adjusting the ad’s color scheme influence the number of people who view the ad?
How does manipulating the ad’s text length affect the average amount of time a user spends on the landing page?
How does changing the ad’s placement on the page affect the amount of money spent on the ad?
How does varying the ad’s targeting parameters affect the number of impressions?
How does altering the ad’s call-to-action language impact the click-through rate?

Quantitative question examples for social media monitoring

Quantitative market research can be applied to measure and analyze the impact of social media on a brand’s awareness, engagement, and reputation . By tracking key metrics such as the number of followers, impressions, and shares, brands can:

Assess the success of their social media campaigns
Understand what content resonates with customers
Spot potential areas for improvement
How often are people talking about our brand on social media channels?
How many times has our brand been mentioned in the past month?
What are the most popular topics related to our brand on social media?
What is the sentiment associated with our brand across social media channels?
How do our competitors compare in terms of social media presence?
What is the average response time for customer inquiries on social media?
What percentage of followers are actively engaging with our brand?
What are the most popular hashtags associated with our brand?
What types of content generate the most engagement on social media?
How does our brand compare to our competitors in terms of reach and engagement on social media?

Example of quantitative research question and answer: social media monitoring

‍♀️ Question: How does our brand compare to our competitors in terms of reach and engagement on social media?

Insight sought: The social channels that most effectively drive traffic and engagement in my market

✅ How it’s done: Similarweb Digital Research Intelligence shows you a marketing channels overview at both an industry and market level. With it, you can view the most effective social media channels in any industry and drill down to compare social performance across a custom group of competitors or an individual company.

Here, I’ve taken the five closest rivals in my market and clicked to expand social media channel data. Wells Fargo and Bank of America have generated the highest traffic volume from social media, with over 6.6 million referrals this year. Next, I can see the exact percentage of traffic generated by each channel and its relative share of traffic for each competitor. This shows me the most effective channels are YouTube, Facebook, LinkedIn, and Reddit – in that order.

In 30-seconds, I’ve discovered the following:

YouTube is the most popular social network in my market.
Facebook and LinkedIn are the second and third most popular channels.
Wells Fargo is my primary target for a more in-depth review, with the highest performance on the top two channels.
Bank of America is outperforming all key players significantly on LinkedIn.
American Express has found a high referral opportunity on Reddit that others have been unable to match.

Power-up Your Market Research with Similarweb Today

Examples of quantitative research questions for online polls

This is one of the oldest known uses of quantitative market research. It dates back to the 19th century when they were first used in America to try and predict the outcome of the presidential elections.

Polls are just short versions of surveys but provide a point-in-time perspective across a large group of people. You can add a poll to your website as a widget, to an email, or if you’ve got a budget to spend, you might use a company like YouGov to add questions to one of their online polls and distribute it to an audience en-masse.

What is your annual income?
In what age group do you fall?
On average, how much do you spend on our products per month?
How likely are you to recommend our products to others?
How satisfied are you with our customer service?
How likely are you to purchase our products in the future?
On a scale of 1 to 10, how important is price when it comes to buying our products?
How likely are you to use our products in the next six months?
What other brands of products do you purchase?
How would you rate our products compared to our competitors?

Quantitative research questions for eye tracking studies

These research studies measure how people look and respond to different websites or ad elements. It’s traditionally an example of quantitative research used by enterprise firms but is becoming more common in the SMB space due to easier access to such technologies.

How much time do participants spend looking at each visual element of the product or ad?
How does the order of presentation affect the impact of time spent looking at each visual element?
How does the size of the visual elements affect the amount of time spent looking at them?
What is the average time participants spend looking at the product or ad as a whole?
What is the average number of fixations participants make when looking at the product or ad?
Are there any visual elements that participants consistently ignore?
How does the product’s design or advertising affect the average number of fixations?
How do different types of participants (age, gender, etc.) interact with the product or ad differently?
Is there a correlation between the amount of time spent looking at the product or ad and the participants’ purchase decision?
How does the user’s experience with similar products or ads affect the amount of time spent looking at the current product or ad?

Quantitative question examples for customer segmentation

Segmentation is becoming more important as organizations large and small seek to offer more personalized experiences. Effective segmentation helps businesses understand their customer’s needs–which can result in more targeted marketing, increased conversions, higher levels of loyalty, and better brand awareness.

quantitative research questions for segmentation

If you’re just starting to segment your market, and want to know the best quantitative research questions to ask to help you do this, here are 20 to choose from.

Examples of quantitative research questions to segment customers

What is your age range?
What is your annual household income?
What is your preferred online shopping method?
What is your occupation?
What types of products do you typically purchase?
Are you a frequent shopper?
How often do you purchase products online?
What is your typical budget for online purchases?
What is your primary motivation for purchasing products online?
What factors influence your decision to purchase a product online?
What device do you use most often when shopping online?
What type of product categories are you most interested in?
Do you prefer to shop online for convenience or for a better price?
What type of discounts or promotions do you look for when making online purchases?
How do you prefer to receive notifications about product promotions or discounts?
What type of payment methods do you prefer when shopping online?
What methods do you use to compare different products and prices when shopping online?
What type of customer service do you expect when shopping online?
What type of product reviews do you consider when making online purchases?
How do you prefer to interact with a brand when shopping online?

Examples of quantitative research questions for analyzing customer segments

What is the average age of customers in each segment?
How do spending habits vary across customer segments ?
What is the average length of time customers spend in each segment?
How does loyalty vary across customer segments?
What is the average purchase size in each segment?
What is the average frequency of purchases in each segment?
What is the average customer lifetime value in each segment?
How does customer satisfaction vary across customer segments?
What is the average response rate to campaigns in each segment?
How does customer engagement vary across customer segments?

These questions are ideal to ask once you’ve already defined your segments. We’ve written a useful post that covers the ins and outs of what market segmentation is and how to do it.

Additional applications of quantitative research questions

I’ve covered ten use cases for quantitative questions in detail. Still, there are other instances where you can put quantitative research to good use.

Product usage studies: Measure how customers use a product or service.

Preference testing: Testing of customer preferences for different products or services.

Sales analysis: Analysis of sales data to identify trends and patterns.

Distribution analysis: Analyzing distribution channels to determine the most efficient and effective way to reach customers.

Focus groups: Groups of consumers brought together to discuss and provide feedback on a particular product, service, or marketing campaign.

Consumer interviews: Conducted with customers to understand their behavior and preferences better.

Mystery shopping: Mystery shoppers are sent to stores to measure customer service levels and product availability.

Conjoint analysis: Analysis of how consumers value different attributes of a product or service.

Regression analysis: Statistical analysis used to identify relationships between different variables.

A/B testing: Testing two or more different versions of a product or service to determine which one performs better.

Brand equity studies: Measure, compare and analyze brand recognition, loyalty, and consumer perception.

Exit surveys: Collect numerical data to analyze employee experience and reasons for leaving, providing insight into how to improve the work environment and retain employees.

Price sensitivity testing: Measuring responses to different pricing models to find the optimal pricing model, and identify areas if and where discounts or incentives might be beneficial.

Quantitative market research survey examples

A recent GreenBook study shows that 89% of people in the market research industry use online surveys frequently–and for good reason. They’re quick and easy to set up, the cost is minimal, and they’re highly scalable too.

Quantitative market research method examples

Questions are always formatted to provide close-ended answers that can be quantified. If you wish to collect free-text responses, this ventures into the realm of qualitative research . Here are a few examples.

Brand Loyalty Surveys: Companies use online surveys to measure customers’ loyalty to their brand. They include questions about how long an individual has been a customer, their overall satisfaction with the service or product, and the likelihood of them recommending the brand to others.

Customer Satisfaction Surveys: These surveys may include questions about the customer’s experience, their overall satisfaction, and the likelihood they will recommend a product or service to others.

Pricing Studies: This type of research reveals how customers value their products or services. These surveys may include questions about the customer’s willingness to pay for the product, the customer’s perception of the price and value, and their comparison of the price to other similar items.

Product/Service Usage Studies: These surveys measure how customers use their products or services. They can include questions about how often customers use a product, their preferred features, and overall satisfaction.

Here’s an example of a typical survey we’ve used when testing out potential features with groups of clients. After they’ve had the chance to use the feature for a period, we send a short survey, then use the feedback to determine the viability of the feature for future release.

Employee Experience Surveys: Another great example of quantitative data in action, and one we use at Similarweb to measure employee satisfaction. Many online platforms are available to help you conduct them; here, we use Culture AMP . The ability to manipulate the data, spot patterns or trends, then identify the core successes and development areas are astounding.

Qualitative customer experience example Culture AMP

How to answer quantitative research questions with Similarweb

For the vast majority of applications I’ve covered in this post, there’s a more modern, quicker, and more efficient way to obtain similar insights online. Gone are the days when companies need to use expensive outdated data or pay hefty sums of money to market research firms to conduct broad studies to get the answers they need.

By this point, I hope you’ve seen how quick and easy it is to use Similarweb to do market research the modern way. But I’ve only scratched the surface of its capabilities.

Take two to watch this introductory video and see what else you can uncover.

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Similarweb’s suite of market intelligence solutions offers unbiased, accurate, honest insights you can trust. With a world of data at your fingertips, use Similarweb Research Intelligence to uncover facts that help inform your research and strengthen your position.

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Wrapping up

Today’s markets change at lightning speed. To keep up and succeed, companies need access to insights and intel they can depend on to be timely and on-point. While quantitative market research questions can and should always be asked, it’s important to leverage technology to increase your speed to insight, and thus improve reaction times and response to market shifts.

What is quantitative market research?

Quantitative market research is a form of research that uses numerical data to gain insights into the behavior and preferences of customers. It is used to measure and track the performance of products, services, and campaigns.

How does quantitative market research help businesses?

Quantitative market research can help businesses identify customer trends, measure customer satisfaction, and develop effective marketing strategies. It can also provide valuable insights into customer behavior, preferences, and attitudes.

What types of questions should be included in a quantitative market research survey?

Questions in a quantitative market research survey should be focused, clear, and specific. Questions should be structured to collect quantitative data, such as numbers, percentages, or frequency of responses.

What methods can be used to collect quantitative market research data?

Common methods used to collect quantitative market research data include surveys, interviews, focus groups, polls, and online questionnaires.

What are the advantages and disadvantages of using quantitative market research?

The advantages of using quantitative market research include the ability to collect data quickly, the ability to analyze data in a structured way, and the ability to identify trends. Disadvantages include the potential for bias, the cost of collecting data, and the difficulty in interpreting results.

by Liz March

Digital Research Specialist

Liz March has 15 years of experience in content creation. She enjoys the outdoors, F1, and reading, and is pursuing a BSc in Environmental Science.

Importance of Market Research: 9 Reasons Why It’s Crucial for Your Business

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Unlocking Consumer Behavior: What Makes Your Customers Tick?

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In This Article Expand or collapse the "in this article" section Research Methods for Studying Daily Life

Introduction, general overviews.

Study Designs and Sampling Methods
Advantages and Limitations of Daily-Life Methods
Sampling and Measurement Considerations
Technology/Equipment for Daily Assessments
Additional Considerations and Future Directions

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Research Methods for Studying Daily Life by Carla Arredondo , Gloria Luong LAST REVIEWED: 24 April 2019 LAST MODIFIED: 24 April 2019 DOI: 10.1093/obo/9780199828340-0243

Methods for studying daily life have blossomed since the 1980s. Although these methods have been around for years, their popularity is always increasing as technological innovations have made the use of these methods easier and more reliable to employ. Methods for studying daily life typically include taking repeated real-time assessments of individual behaviors, physiology, and/or psychological experiences, over the course of an individual’s everyday life. These methods include experience sampling methodology (ESM), ecological momentary assessments (EMA), ambulatory assessments (AA), and daily diary or day reconstruction methods. All of these methods include repeated or detailed assessments of daily- life experiences but vary in terms of the frequency of assessments, technological tools to administer assessments, and timing of assessments (e.g., real time assessments versus retrospective recall). Given that these methods are intended to capture observations of psychological experiences in daily life, they require careful consideration of study design, measurements, and assessment tools. This article will provide a general overview of daily-life methods, including discussions about the different study designs and sampling methods. Furthermore, it will describe the advantages and limitations of using these methods along with examples of empirical studies that illustrate the usefulness of these techniques. It will also provide information on important considerations for sampling and measuring experiences in daily life and provide examples of the technology available for daily-life assessments.

Mehl and Conner 2012 is an all-encompassing review that discusses theoretical, methodological, and statistical considerations for conducting daily-life studies. Conner and Lehman 2012 focuses on providing practical advice for designing and conducting daily-life studies, while Stone and Shiffman 2002 outlines standardized reporting guidelines for researchers and provides recommendations for the information that should be included in study reports. Broderick, et al. 2003 and Green, et al. 2006 discuss issues of participant compliance and provide examples of how to monitor and improve participant compliance in daily-life studies. Barta, et al. 2012 discusses issues of measurement reactivity, whereby measurements bring about changes in study participants, and Conner and Reid 2012 is an example of testing for measurement reactivity. Lastly, Bolger, et al. 2003 provides an outline of areas of research that will need further investigation as intensive longitudinal designs become more prevalent.

Barta, W. D., H. Tennen, and M. D. Litt. 2012. Measurement reactivity in diary research. In Handbook of research methods for studying daily life . Edited by M. R. Mehl and T. S. Conner, 89–107. New York: Guildford Press.

Reviews factors that can affect measurement of constructs in daily-life studies. Discusses some of the sources of measurement reactivity, such as social desirability of the construct under investigation and conditions that influence reactivity of self-monitoring, such as participant motivation. They conclude with a review of studies demonstrating mixed findings on measurement reactivity and recommend that more daily-life studies explicitly test for measurement reactivity.

Bolger, N., A. Davis, and E. Rafaeli. 2003. Diary methods: Capturing life as it is lived. Annual Review of Psychology 54:579–616.

DOI: 10.1146/annurev.psych.54.101601.145030

Discusses areas of research that will need further consideration as intensive longitudinal study designs become more common. The article also discusses using technology to monitor objective measurements, such as heart rate, in conjunction with subjective experiences (i.e., mood). Also covered is the need to develop and test measures that can capture within-person changes and ideas for formulating research questions to further understand how these processes unfold in everyday life.

Broderick, J., J. Schwartz, S. Shiffman, M. Hufford, and A. Stone. 2003. Signaling does not adequately improve diary compliance. Annals of Behavioral Medicine 26:139–148.

DOI: 10.1207/S15324796ABM2602_06

Tested the extent to which signaling participants, via a programmed wristwatch, improved compliance in a twenty-four-day experience sampling study of individuals with chronic pain. The study used photo sensors to detect when diaries were opened and closed by participants to make an entry, and this information was cross-referenced with participant self-reports of compliance.

Conner, T. S., and B. Lehman. 2012. Getting started: Launching a study in daily life. In Handbook of research methods for studying daily life . Edited by M. R. Mehl and T. S. Conner, 89–107. New York: Guildford Press.

Provides an overview of important considerations for designing and conducting daily-life studies. It begins with preliminary considerations, such as participant characteristics, and moves into sampling strategies and platforms. Practical concerns, such as ethical considerations, are also discussed.

Conner, T. S., and K. A. Reid. 2012. Effects of intensive mobile happiness reporting in daily life. Social Psychology and Personality Science 3:315–323.

DOI: 10.1177/1948550611419677

An example of an experience sampling study that explicitly tested measurement reactivity. The study examined the extent to which there was measurement reactivity in a measure of happiness. Results demonstrate that overall the measure in question did not show reactivity. However, participant characteristics, such as depressive symptoms and trait neuroticism, contributed to measurement reactivity.

Green, A. S., E. Rafaeli, N. Bolger, P. E. Shrout, and H. T. Reis. 2006. Paper or plastic? Data equivalence in paper and electronic diaries. Psychological Methods 11:87–105.

DOI: 10.1037/1082-989X.11.1.87

See this article for a brief review of concerns regarding participant compliance in diary studies (pp. 87–88). The article also discusses other issues such as important considerations for improving the data quality from diary studies, recommendations for defining compliance, and individual differences in compliance (pp. 102–104). The article concludes with recommendations for improving diary studies.

Mehl, M. R., and T. S. Conner, eds. 2012. Handbook of research methods for studying daily life . New York: Guildford Press.

This book provides an all-encompassing review for researchers conducting daily-life studies. It is a resource for conducting high-quality research and provides guidelines to select and implement methods for studying daily life. The book begins with fundamental theoretical and methodological considerations for conducting these studies and then reviews statistical techniques that can be used to analyze these data. The book concludes with examples of these methods and techniques across different sub-fields in psychology.

Stone, A. A., and S. Shiffman. 2002 Capturing momentary, self-report data: A proposal for reporting guidelines. Guidelines for Momentary Research 24:236–243.

Proposes criteria for collecting momentary data. Argues that strategies for sampling daily-life data should be based on theoretical, statistical, and practical considerations of the phenomena in question that allow researchers to adequately collect data for hypothesis testing. The article also provides recommendations on reporting guidelines to facilitate study replication.

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Learning Module: Senior High School Quantitative Research

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Systematic Observation: Engaging Researchers in the Study of Daily Life as It Is Lived

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What Is Quantitative Research? | Definition, Uses & Methods

What Is Quantitative Research? | Definition, Uses & Methods

Published on June 12, 2020 by Pritha Bhandari . Revised on June 22, 2023.

Quantitative research is the process of collecting and analyzing numerical data. It can be used to find patterns and averages, make predictions, test causal relationships, and generalize results to wider populations.

Quantitative research is the opposite of qualitative research , which involves collecting and analyzing non-numerical data (e.g., text, video, or audio).

Quantitative research is widely used in the natural and social sciences: biology, chemistry, psychology, economics, sociology, marketing, etc.

What is the demographic makeup of Singapore in 2020?
How has the average temperature changed globally over the last century?
Does environmental pollution affect the prevalence of honey bees?
Does working from home increase productivity for people with long commutes?

Quantitative research methods, quantitative data analysis, advantages of quantitative research, disadvantages of quantitative research, other interesting articles, frequently asked questions about quantitative research.

You can use quantitative research methods for descriptive, correlational or experimental research.

In descriptive research , you simply seek an overall summary of your study variables.
In correlational research , you investigate relationships between your study variables.
In experimental research , you systematically examine whether there is a cause-and-effect relationship between variables.

Correlational and experimental research can both be used to formally test hypotheses , or predictions, using statistics. The results may be generalized to broader populations based on the sampling method used.

To collect quantitative data, you will often need to use operational definitions that translate abstract concepts (e.g., mood) into observable and quantifiable measures (e.g., self-ratings of feelings and energy levels).

Quantitative research methods
Research method	How to use	Example
	Control or manipulate an to measure its effect on a dependent variable.	To test whether an intervention can reduce procrastination in college students, you give equal-sized groups either a procrastination intervention or a comparable task. You compare self-ratings of procrastination behaviors between the groups after the intervention.
	Ask questions of a group of people in-person, over-the-phone or online.	You distribute with rating scales to first-year international college students to investigate their experiences of culture shock.
(Systematic) observation	Identify a behavior or occurrence of interest and monitor it in its natural setting.	To study college classroom participation, you sit in on classes to observe them, counting and recording the prevalence of active and passive behaviors by students from different backgrounds.
Secondary research	Collect data that has been gathered for other purposes e.g., national surveys or historical records.	To assess whether attitudes towards climate change have changed since the 1980s, you collect relevant questionnaire data from widely available .

Note that quantitative research is at risk for certain research biases , including information bias , omitted variable bias , sampling bias , or selection bias . Be sure that you’re aware of potential biases as you collect and analyze your data to prevent them from impacting your work too much.

Prevent plagiarism. Run a free check.

Once data is collected, you may need to process it before it can be analyzed. For example, survey and test data may need to be transformed from words to numbers. Then, you can use statistical analysis to answer your research questions .

Descriptive statistics will give you a summary of your data and include measures of averages and variability. You can also use graphs, scatter plots and frequency tables to visualize your data and check for any trends or outliers.

Using inferential statistics , you can make predictions or generalizations based on your data. You can test your hypothesis or use your sample data to estimate the population parameter .

First, you use descriptive statistics to get a summary of the data. You find the mean (average) and the mode (most frequent rating) of procrastination of the two groups, and plot the data to see if there are any outliers.

You can also assess the reliability and validity of your data collection methods to indicate how consistently and accurately your methods actually measured what you wanted them to.

Quantitative research is often used to standardize data collection and generalize findings . Strengths of this approach include:

Replication

Repeating the study is possible because of standardized data collection protocols and tangible definitions of abstract concepts.

Direct comparisons of results

The study can be reproduced in other cultural settings, times or with different groups of participants. Results can be compared statistically.

Large samples

Data from large samples can be processed and analyzed using reliable and consistent procedures through quantitative data analysis.

Hypothesis testing

Using formalized and established hypothesis testing procedures means that you have to carefully consider and report your research variables, predictions, data collection and testing methods before coming to a conclusion.

Despite the benefits of quantitative research, it is sometimes inadequate in explaining complex research topics. Its limitations include:

Superficiality

Using precise and restrictive operational definitions may inadequately represent complex concepts. For example, the concept of mood may be represented with just a number in quantitative research, but explained with elaboration in qualitative research.

Narrow focus

Predetermined variables and measurement procedures can mean that you ignore other relevant observations.

Structural bias

Despite standardized procedures, structural biases can still affect quantitative research. Missing data , imprecise measurements or inappropriate sampling methods are biases that can lead to the wrong conclusions.

Lack of context

Quantitative research often uses unnatural settings like laboratories or fails to consider historical and cultural contexts that may affect data collection and results.

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If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

Chi square goodness of fit test
Degrees of freedom
Null hypothesis
Discourse analysis
Control groups
Mixed methods research
Non-probability sampling
Inclusion and exclusion criteria

Research bias

Rosenthal effect
Implicit bias
Cognitive bias
Selection bias
Negativity bias
Status quo bias

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .

Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organizations.

Operationalization means turning abstract conceptual ideas into measurable observations.

For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioral avoidance of crowded places, or physical anxiety symptoms in social situations.

Before collecting data , it’s important to consider how you will operationalize the variables that you want to measure.

Reliability and validity are both about how well a method measures something:

Reliability refers to the consistency of a measure (whether the results can be reproduced under the same conditions).
Validity refers to the accuracy of a measure (whether the results really do represent what they are supposed to measure).

If you are doing experimental research, you also have to consider the internal and external validity of your experiment.

Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is used by scientists to test specific predictions, called hypotheses , by calculating how likely it is that a pattern or relationship between variables could have arisen by chance.

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A Practical Guide to Writing Quantitative and Qualitative Research Questions and Hypotheses in Scholarly Articles

Edward barroga.

1 Department of General Education, Graduate School of Nursing Science, St. Luke’s International University, Tokyo, Japan.

Glafera Janet Matanguihan

2 Department of Biological Sciences, Messiah University, Mechanicsburg, PA, USA.

The development of research questions and the subsequent hypotheses are prerequisites to defining the main research purpose and specific objectives of a study. Consequently, these objectives determine the study design and research outcome. The development of research questions is a process based on knowledge of current trends, cutting-edge studies, and technological advances in the research field. Excellent research questions are focused and require a comprehensive literature search and in-depth understanding of the problem being investigated. Initially, research questions may be written as descriptive questions which could be developed into inferential questions. These questions must be specific and concise to provide a clear foundation for developing hypotheses. Hypotheses are more formal predictions about the research outcomes. These specify the possible results that may or may not be expected regarding the relationship between groups. Thus, research questions and hypotheses clarify the main purpose and specific objectives of the study, which in turn dictate the design of the study, its direction, and outcome. Studies developed from good research questions and hypotheses will have trustworthy outcomes with wide-ranging social and health implications.

INTRODUCTION

Scientific research is usually initiated by posing evidenced-based research questions which are then explicitly restated as hypotheses. 1 , 2 The hypotheses provide directions to guide the study, solutions, explanations, and expected results. 3 , 4 Both research questions and hypotheses are essentially formulated based on conventional theories and real-world processes, which allow the inception of novel studies and the ethical testing of ideas. 5 , 6

It is crucial to have knowledge of both quantitative and qualitative research 2 as both types of research involve writing research questions and hypotheses. 7 However, these crucial elements of research are sometimes overlooked; if not overlooked, then framed without the forethought and meticulous attention it needs. Planning and careful consideration are needed when developing quantitative or qualitative research, particularly when conceptualizing research questions and hypotheses. 4

There is a continuing need to support researchers in the creation of innovative research questions and hypotheses, as well as for journal articles that carefully review these elements. 1 When research questions and hypotheses are not carefully thought of, unethical studies and poor outcomes usually ensue. Carefully formulated research questions and hypotheses define well-founded objectives, which in turn determine the appropriate design, course, and outcome of the study. This article then aims to discuss in detail the various aspects of crafting research questions and hypotheses, with the goal of guiding researchers as they develop their own. Examples from the authors and peer-reviewed scientific articles in the healthcare field are provided to illustrate key points.

DEFINITIONS AND RELATIONSHIP OF RESEARCH QUESTIONS AND HYPOTHESES

A research question is what a study aims to answer after data analysis and interpretation. The answer is written in length in the discussion section of the paper. Thus, the research question gives a preview of the different parts and variables of the study meant to address the problem posed in the research question. 1 An excellent research question clarifies the research writing while facilitating understanding of the research topic, objective, scope, and limitations of the study. 5

On the other hand, a research hypothesis is an educated statement of an expected outcome. This statement is based on background research and current knowledge. 8 , 9 The research hypothesis makes a specific prediction about a new phenomenon 10 or a formal statement on the expected relationship between an independent variable and a dependent variable. 3 , 11 It provides a tentative answer to the research question to be tested or explored. 4

Hypotheses employ reasoning to predict a theory-based outcome. 10 These can also be developed from theories by focusing on components of theories that have not yet been observed. 10 The validity of hypotheses is often based on the testability of the prediction made in a reproducible experiment. 8

Conversely, hypotheses can also be rephrased as research questions. Several hypotheses based on existing theories and knowledge may be needed to answer a research question. Developing ethical research questions and hypotheses creates a research design that has logical relationships among variables. These relationships serve as a solid foundation for the conduct of the study. 4 , 11 Haphazardly constructed research questions can result in poorly formulated hypotheses and improper study designs, leading to unreliable results. Thus, the formulations of relevant research questions and verifiable hypotheses are crucial when beginning research. 12

CHARACTERISTICS OF GOOD RESEARCH QUESTIONS AND HYPOTHESES

Excellent research questions are specific and focused. These integrate collective data and observations to confirm or refute the subsequent hypotheses. Well-constructed hypotheses are based on previous reports and verify the research context. These are realistic, in-depth, sufficiently complex, and reproducible. More importantly, these hypotheses can be addressed and tested. 13

There are several characteristics of well-developed hypotheses. Good hypotheses are 1) empirically testable 7 , 10 , 11 , 13 ; 2) backed by preliminary evidence 9 ; 3) testable by ethical research 7 , 9 ; 4) based on original ideas 9 ; 5) have evidenced-based logical reasoning 10 ; and 6) can be predicted. 11 Good hypotheses can infer ethical and positive implications, indicating the presence of a relationship or effect relevant to the research theme. 7 , 11 These are initially developed from a general theory and branch into specific hypotheses by deductive reasoning. In the absence of a theory to base the hypotheses, inductive reasoning based on specific observations or findings form more general hypotheses. 10

TYPES OF RESEARCH QUESTIONS AND HYPOTHESES

Research questions and hypotheses are developed according to the type of research, which can be broadly classified into quantitative and qualitative research. We provide a summary of the types of research questions and hypotheses under quantitative and qualitative research categories in Table 1 .

Quantitative research questions	Quantitative research hypotheses
Descriptive research questions	Simple hypothesis
Comparative research questions	Complex hypothesis
Relationship research questions	Directional hypothesis
	Non-directional hypothesis
	Associative hypothesis
	Causal hypothesis
	Null hypothesis
	Alternative hypothesis
	Working hypothesis
	Statistical hypothesis
	Logical hypothesis
	Hypothesis-testing
Qualitative research questions	Qualitative research hypotheses
Contextual research questions	Hypothesis-generating
Descriptive research questions
Evaluation research questions
Explanatory research questions
Exploratory research questions
Generative research questions
Ideological research questions
Ethnographic research questions
Phenomenological research questions
Grounded theory questions
Qualitative case study questions

Research questions in quantitative research

In quantitative research, research questions inquire about the relationships among variables being investigated and are usually framed at the start of the study. These are precise and typically linked to the subject population, dependent and independent variables, and research design. 1 Research questions may also attempt to describe the behavior of a population in relation to one or more variables, or describe the characteristics of variables to be measured ( descriptive research questions ). 1 , 5 , 14 These questions may also aim to discover differences between groups within the context of an outcome variable ( comparative research questions ), 1 , 5 , 14 or elucidate trends and interactions among variables ( relationship research questions ). 1 , 5 We provide examples of descriptive, comparative, and relationship research questions in quantitative research in Table 2 .

Quantitative research questions
Descriptive research question
	- Measures responses of subjects to variables
	- Presents variables to measure, analyze, or assess
	What is the proportion of resident doctors in the hospital who have mastered ultrasonography (response of subjects to a variable) as a diagnostic technique in their clinical training?
Comparative research question
	- Clarifies difference between one group with outcome variable and another group without outcome variable
	Is there a difference in the reduction of lung metastasis in osteosarcoma patients who received the vitamin D adjunctive therapy (group with outcome variable) compared with osteosarcoma patients who did not receive the vitamin D adjunctive therapy (group without outcome variable)?
	- Compares the effects of variables
	How does the vitamin D analogue 22-Oxacalcitriol (variable 1) mimic the antiproliferative activity of 1,25-Dihydroxyvitamin D (variable 2) in osteosarcoma cells?
Relationship research question
	- Defines trends, association, relationships, or interactions between dependent variable and independent variable
	Is there a relationship between the number of medical student suicide (dependent variable) and the level of medical student stress (independent variable) in Japan during the first wave of the COVID-19 pandemic?

Hypotheses in quantitative research

In quantitative research, hypotheses predict the expected relationships among variables. 15 Relationships among variables that can be predicted include 1) between a single dependent variable and a single independent variable ( simple hypothesis ) or 2) between two or more independent and dependent variables ( complex hypothesis ). 4 , 11 Hypotheses may also specify the expected direction to be followed and imply an intellectual commitment to a particular outcome ( directional hypothesis ) 4 . On the other hand, hypotheses may not predict the exact direction and are used in the absence of a theory, or when findings contradict previous studies ( non-directional hypothesis ). 4 In addition, hypotheses can 1) define interdependency between variables ( associative hypothesis ), 4 2) propose an effect on the dependent variable from manipulation of the independent variable ( causal hypothesis ), 4 3) state a negative relationship between two variables ( null hypothesis ), 4 , 11 , 15 4) replace the working hypothesis if rejected ( alternative hypothesis ), 15 explain the relationship of phenomena to possibly generate a theory ( working hypothesis ), 11 5) involve quantifiable variables that can be tested statistically ( statistical hypothesis ), 11 6) or express a relationship whose interlinks can be verified logically ( logical hypothesis ). 11 We provide examples of simple, complex, directional, non-directional, associative, causal, null, alternative, working, statistical, and logical hypotheses in quantitative research, as well as the definition of quantitative hypothesis-testing research in Table 3 .

Quantitative research hypotheses
Simple hypothesis
	- Predicts relationship between single dependent variable and single independent variable
	If the dose of the new medication (single independent variable) is high, blood pressure (single dependent variable) is lowered.
Complex hypothesis
	- Foretells relationship between two or more independent and dependent variables
	The higher the use of anticancer drugs, radiation therapy, and adjunctive agents (3 independent variables), the higher would be the survival rate (1 dependent variable).
Directional hypothesis
	- Identifies study direction based on theory towards particular outcome to clarify relationship between variables
	Privately funded research projects will have a larger international scope (study direction) than publicly funded research projects.
Non-directional hypothesis
	- Nature of relationship between two variables or exact study direction is not identified
	- Does not involve a theory
	Women and men are different in terms of helpfulness. (Exact study direction is not identified)
Associative hypothesis
	- Describes variable interdependency
	- Change in one variable causes change in another variable
	A larger number of people vaccinated against COVID-19 in the region (change in independent variable) will reduce the region’s incidence of COVID-19 infection (change in dependent variable).
Causal hypothesis
	- An effect on dependent variable is predicted from manipulation of independent variable
	A change into a high-fiber diet (independent variable) will reduce the blood sugar level (dependent variable) of the patient.
Null hypothesis
	- A negative statement indicating no relationship or difference between 2 variables
	There is no significant difference in the severity of pulmonary metastases between the new drug (variable 1) and the current drug (variable 2).
Alternative hypothesis
	- Following a null hypothesis, an alternative hypothesis predicts a relationship between 2 study variables
	The new drug (variable 1) is better on average in reducing the level of pain from pulmonary metastasis than the current drug (variable 2).
Working hypothesis
	- A hypothesis that is initially accepted for further research to produce a feasible theory
	Dairy cows fed with concentrates of different formulations will produce different amounts of milk.
Statistical hypothesis
	- Assumption about the value of population parameter or relationship among several population characteristics
	- Validity tested by a statistical experiment or analysis
	The mean recovery rate from COVID-19 infection (value of population parameter) is not significantly different between population 1 and population 2.
	There is a positive correlation between the level of stress at the workplace and the number of suicides (population characteristics) among working people in Japan.
Logical hypothesis
	- Offers or proposes an explanation with limited or no extensive evidence
	If healthcare workers provide more educational programs about contraception methods, the number of adolescent pregnancies will be less.
Hypothesis-testing (Quantitative hypothesis-testing research)
	- Quantitative research uses deductive reasoning.
	- This involves the formation of a hypothesis, collection of data in the investigation of the problem, analysis and use of the data from the investigation, and drawing of conclusions to validate or nullify the hypotheses.

Research questions in qualitative research

Unlike research questions in quantitative research, research questions in qualitative research are usually continuously reviewed and reformulated. The central question and associated subquestions are stated more than the hypotheses. 15 The central question broadly explores a complex set of factors surrounding the central phenomenon, aiming to present the varied perspectives of participants. 15

There are varied goals for which qualitative research questions are developed. These questions can function in several ways, such as to 1) identify and describe existing conditions ( contextual research question s); 2) describe a phenomenon ( descriptive research questions ); 3) assess the effectiveness of existing methods, protocols, theories, or procedures ( evaluation research questions ); 4) examine a phenomenon or analyze the reasons or relationships between subjects or phenomena ( explanatory research questions ); or 5) focus on unknown aspects of a particular topic ( exploratory research questions ). 5 In addition, some qualitative research questions provide new ideas for the development of theories and actions ( generative research questions ) or advance specific ideologies of a position ( ideological research questions ). 1 Other qualitative research questions may build on a body of existing literature and become working guidelines ( ethnographic research questions ). Research questions may also be broadly stated without specific reference to the existing literature or a typology of questions ( phenomenological research questions ), may be directed towards generating a theory of some process ( grounded theory questions ), or may address a description of the case and the emerging themes ( qualitative case study questions ). 15 We provide examples of contextual, descriptive, evaluation, explanatory, exploratory, generative, ideological, ethnographic, phenomenological, grounded theory, and qualitative case study research questions in qualitative research in Table 4 , and the definition of qualitative hypothesis-generating research in Table 5 .

Qualitative research questions
Contextual research question
	- Ask the nature of what already exists
	- Individuals or groups function to further clarify and understand the natural context of real-world problems
	What are the experiences of nurses working night shifts in healthcare during the COVID-19 pandemic? (natural context of real-world problems)
Descriptive research question
	- Aims to describe a phenomenon
	What are the different forms of disrespect and abuse (phenomenon) experienced by Tanzanian women when giving birth in healthcare facilities?
Evaluation research question
	- Examines the effectiveness of existing practice or accepted frameworks
	How effective are decision aids (effectiveness of existing practice) in helping decide whether to give birth at home or in a healthcare facility?
Explanatory research question
	- Clarifies a previously studied phenomenon and explains why it occurs
	Why is there an increase in teenage pregnancy (phenomenon) in Tanzania?
Exploratory research question
	- Explores areas that have not been fully investigated to have a deeper understanding of the research problem
	What factors affect the mental health of medical students (areas that have not yet been fully investigated) during the COVID-19 pandemic?
Generative research question
	- Develops an in-depth understanding of people’s behavior by asking ‘how would’ or ‘what if’ to identify problems and find solutions
	How would the extensive research experience of the behavior of new staff impact the success of the novel drug initiative?
Ideological research question
	- Aims to advance specific ideas or ideologies of a position
	Are Japanese nurses who volunteer in remote African hospitals able to promote humanized care of patients (specific ideas or ideologies) in the areas of safe patient environment, respect of patient privacy, and provision of accurate information related to health and care?
Ethnographic research question
	- Clarifies peoples’ nature, activities, their interactions, and the outcomes of their actions in specific settings
	What are the demographic characteristics, rehabilitative treatments, community interactions, and disease outcomes (nature, activities, their interactions, and the outcomes) of people in China who are suffering from pneumoconiosis?
Phenomenological research question
	- Knows more about the phenomena that have impacted an individual
	What are the lived experiences of parents who have been living with and caring for children with a diagnosis of autism? (phenomena that have impacted an individual)
Grounded theory question
	- Focuses on social processes asking about what happens and how people interact, or uncovering social relationships and behaviors of groups
	What are the problems that pregnant adolescents face in terms of social and cultural norms (social processes), and how can these be addressed?
Qualitative case study question
	- Assesses a phenomenon using different sources of data to answer “why” and “how” questions
	- Considers how the phenomenon is influenced by its contextual situation.
	How does quitting work and assuming the role of a full-time mother (phenomenon assessed) change the lives of women in Japan?

Qualitative research hypotheses
Hypothesis-generating (Qualitative hypothesis-generating research)
	- Qualitative research uses inductive reasoning.
	- This involves data collection from study participants or the literature regarding a phenomenon of interest, using the collected data to develop a formal hypothesis, and using the formal hypothesis as a framework for testing the hypothesis.
	- Qualitative exploratory studies explore areas deeper, clarifying subjective experience and allowing formulation of a formal hypothesis potentially testable in a future quantitative approach.

Qualitative studies usually pose at least one central research question and several subquestions starting with How or What . These research questions use exploratory verbs such as explore or describe . These also focus on one central phenomenon of interest, and may mention the participants and research site. 15

Hypotheses in qualitative research

Hypotheses in qualitative research are stated in the form of a clear statement concerning the problem to be investigated. Unlike in quantitative research where hypotheses are usually developed to be tested, qualitative research can lead to both hypothesis-testing and hypothesis-generating outcomes. 2 When studies require both quantitative and qualitative research questions, this suggests an integrative process between both research methods wherein a single mixed-methods research question can be developed. 1

FRAMEWORKS FOR DEVELOPING RESEARCH QUESTIONS AND HYPOTHESES

Research questions followed by hypotheses should be developed before the start of the study. 1 , 12 , 14 It is crucial to develop feasible research questions on a topic that is interesting to both the researcher and the scientific community. This can be achieved by a meticulous review of previous and current studies to establish a novel topic. Specific areas are subsequently focused on to generate ethical research questions. The relevance of the research questions is evaluated in terms of clarity of the resulting data, specificity of the methodology, objectivity of the outcome, depth of the research, and impact of the study. 1 , 5 These aspects constitute the FINER criteria (i.e., Feasible, Interesting, Novel, Ethical, and Relevant). 1 Clarity and effectiveness are achieved if research questions meet the FINER criteria. In addition to the FINER criteria, Ratan et al. described focus, complexity, novelty, feasibility, and measurability for evaluating the effectiveness of research questions. 14

The PICOT and PEO frameworks are also used when developing research questions. 1 The following elements are addressed in these frameworks, PICOT: P-population/patients/problem, I-intervention or indicator being studied, C-comparison group, O-outcome of interest, and T-timeframe of the study; PEO: P-population being studied, E-exposure to preexisting conditions, and O-outcome of interest. 1 Research questions are also considered good if these meet the “FINERMAPS” framework: Feasible, Interesting, Novel, Ethical, Relevant, Manageable, Appropriate, Potential value/publishable, and Systematic. 14

As we indicated earlier, research questions and hypotheses that are not carefully formulated result in unethical studies or poor outcomes. To illustrate this, we provide some examples of ambiguous research question and hypotheses that result in unclear and weak research objectives in quantitative research ( Table 6 ) 16 and qualitative research ( Table 7 ) 17 , and how to transform these ambiguous research question(s) and hypothesis(es) into clear and good statements.

Variables	Unclear and weak statement (Statement 1)	Clear and good statement (Statement 2)	Points to avoid
Research question	Which is more effective between smoke moxibustion and smokeless moxibustion?	“Moreover, regarding smoke moxibustion versus smokeless moxibustion, it remains unclear which is more effective, safe, and acceptable to pregnant women, and whether there is any difference in the amount of heat generated.”	1) Vague and unfocused questions
			2) Closed questions simply answerable by yes or no
			3) Questions requiring a simple choice
Hypothesis	The smoke moxibustion group will have higher cephalic presentation.	“Hypothesis 1. The smoke moxibustion stick group (SM group) and smokeless moxibustion stick group (-SLM group) will have higher rates of cephalic presentation after treatment than the control group.	1) Unverifiable hypotheses
		Hypothesis 2. The SM group and SLM group will have higher rates of cephalic presentation at birth than the control group.	2) Incompletely stated groups of comparison
		Hypothesis 3. There will be no significant differences in the well-being of the mother and child among the three groups in terms of the following outcomes: premature birth, premature rupture of membranes (PROM) at < 37 weeks, Apgar score < 7 at 5 min, umbilical cord blood pH < 7.1, admission to neonatal intensive care unit (NICU), and intrauterine fetal death.”	3) Insufficiently described variables or outcomes
Research objective	To determine which is more effective between smoke moxibustion and smokeless moxibustion.	“The specific aims of this pilot study were (a) to compare the effects of smoke moxibustion and smokeless moxibustion treatments with the control group as a possible supplement to ECV for converting breech presentation to cephalic presentation and increasing adherence to the newly obtained cephalic position, and (b) to assess the effects of these treatments on the well-being of the mother and child.”	1) Poor understanding of the research question and hypotheses
Research objective			2) Insufficient description of population, variables, or study outcomes

a These statements were composed for comparison and illustrative purposes only.

b These statements are direct quotes from Higashihara and Horiuchi. 16

Variables	Unclear and weak statement (Statement 1)	Clear and good statement (Statement 2)	Points to avoid
Research question	Does disrespect and abuse (D&A) occur in childbirth in Tanzania?	How does disrespect and abuse (D&A) occur and what are the types of physical and psychological abuses observed in midwives’ actual care during facility-based childbirth in urban Tanzania?	1) Ambiguous or oversimplistic questions
Research question			2) Questions unverifiable by data collection and analysis
Hypothesis	Disrespect and abuse (D&A) occur in childbirth in Tanzania.	Hypothesis 1: Several types of physical and psychological abuse by midwives in actual care occur during facility-based childbirth in urban Tanzania.	1) Statements simply expressing facts
Hypothesis	Disrespect and abuse (D&A) occur in childbirth in Tanzania.	Hypothesis 2: Weak nursing and midwifery management contribute to the D&A of women during facility-based childbirth in urban Tanzania.	2) Insufficiently described concepts or variables
Research objective	To describe disrespect and abuse (D&A) in childbirth in Tanzania.	“This study aimed to describe from actual observations the respectful and disrespectful care received by women from midwives during their labor period in two hospitals in urban Tanzania.”	1) Statements unrelated to the research question and hypotheses
Research objective			2) Unattainable or unexplorable objectives

a This statement is a direct quote from Shimoda et al. 17

The other statements were composed for comparison and illustrative purposes only.

CONSTRUCTING RESEARCH QUESTIONS AND HYPOTHESES

To construct effective research questions and hypotheses, it is very important to 1) clarify the background and 2) identify the research problem at the outset of the research, within a specific timeframe. 9 Then, 3) review or conduct preliminary research to collect all available knowledge about the possible research questions by studying theories and previous studies. 18 Afterwards, 4) construct research questions to investigate the research problem. Identify variables to be accessed from the research questions 4 and make operational definitions of constructs from the research problem and questions. Thereafter, 5) construct specific deductive or inductive predictions in the form of hypotheses. 4 Finally, 6) state the study aims . This general flow for constructing effective research questions and hypotheses prior to conducting research is shown in Fig. 1 .

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Research questions are used more frequently in qualitative research than objectives or hypotheses. 3 These questions seek to discover, understand, explore or describe experiences by asking “What” or “How.” The questions are open-ended to elicit a description rather than to relate variables or compare groups. The questions are continually reviewed, reformulated, and changed during the qualitative study. 3 Research questions are also used more frequently in survey projects than hypotheses in experiments in quantitative research to compare variables and their relationships.

Hypotheses are constructed based on the variables identified and as an if-then statement, following the template, ‘If a specific action is taken, then a certain outcome is expected.’ At this stage, some ideas regarding expectations from the research to be conducted must be drawn. 18 Then, the variables to be manipulated (independent) and influenced (dependent) are defined. 4 Thereafter, the hypothesis is stated and refined, and reproducible data tailored to the hypothesis are identified, collected, and analyzed. 4 The hypotheses must be testable and specific, 18 and should describe the variables and their relationships, the specific group being studied, and the predicted research outcome. 18 Hypotheses construction involves a testable proposition to be deduced from theory, and independent and dependent variables to be separated and measured separately. 3 Therefore, good hypotheses must be based on good research questions constructed at the start of a study or trial. 12

In summary, research questions are constructed after establishing the background of the study. Hypotheses are then developed based on the research questions. Thus, it is crucial to have excellent research questions to generate superior hypotheses. In turn, these would determine the research objectives and the design of the study, and ultimately, the outcome of the research. 12 Algorithms for building research questions and hypotheses are shown in Fig. 2 for quantitative research and in Fig. 3 for qualitative research.

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EXAMPLES OF RESEARCH QUESTIONS FROM PUBLISHED ARTICLES

EXAMPLE 1. Descriptive research question (quantitative research)
- Presents research variables to be assessed (distinct phenotypes and subphenotypes)
“BACKGROUND: Since COVID-19 was identified, its clinical and biological heterogeneity has been recognized. Identifying COVID-19 phenotypes might help guide basic, clinical, and translational research efforts.
RESEARCH QUESTION: Does the clinical spectrum of patients with COVID-19 contain distinct phenotypes and subphenotypes? ” 19
EXAMPLE 2. Relationship research question (quantitative research)
- Shows interactions between dependent variable (static postural control) and independent variable (peripheral visual field loss)
“Background: Integration of visual, vestibular, and proprioceptive sensations contributes to postural control. People with peripheral visual field loss have serious postural instability. However, the directional specificity of postural stability and sensory reweighting caused by gradual peripheral visual field loss remain unclear.
Research question: What are the effects of peripheral visual field loss on static postural control ?” 20
EXAMPLE 3. Comparative research question (quantitative research)
- Clarifies the difference among groups with an outcome variable (patients enrolled in COMPERA with moderate PH or severe PH in COPD) and another group without the outcome variable (patients with idiopathic pulmonary arterial hypertension (IPAH))
“BACKGROUND: Pulmonary hypertension (PH) in COPD is a poorly investigated clinical condition.
RESEARCH QUESTION: Which factors determine the outcome of PH in COPD?
STUDY DESIGN AND METHODS: We analyzed the characteristics and outcome of patients enrolled in the Comparative, Prospective Registry of Newly Initiated Therapies for Pulmonary Hypertension (COMPERA) with moderate or severe PH in COPD as defined during the 6th PH World Symposium who received medical therapy for PH and compared them with patients with idiopathic pulmonary arterial hypertension (IPAH) .” 21
EXAMPLE 4. Exploratory research question (qualitative research)
- Explores areas that have not been fully investigated (perspectives of families and children who receive care in clinic-based child obesity treatment) to have a deeper understanding of the research problem
“Problem: Interventions for children with obesity lead to only modest improvements in BMI and long-term outcomes, and data are limited on the perspectives of families of children with obesity in clinic-based treatment. This scoping review seeks to answer the question: What is known about the perspectives of families and children who receive care in clinic-based child obesity treatment? This review aims to explore the scope of perspectives reported by families of children with obesity who have received individualized outpatient clinic-based obesity treatment.” 22
EXAMPLE 5. Relationship research question (quantitative research)
- Defines interactions between dependent variable (use of ankle strategies) and independent variable (changes in muscle tone)
“Background: To maintain an upright standing posture against external disturbances, the human body mainly employs two types of postural control strategies: “ankle strategy” and “hip strategy.” While it has been reported that the magnitude of the disturbance alters the use of postural control strategies, it has not been elucidated how the level of muscle tone, one of the crucial parameters of bodily function, determines the use of each strategy. We have previously confirmed using forward dynamics simulations of human musculoskeletal models that an increased muscle tone promotes the use of ankle strategies. The objective of the present study was to experimentally evaluate a hypothesis: an increased muscle tone promotes the use of ankle strategies. Research question: Do changes in the muscle tone affect the use of ankle strategies ?” 23

EXAMPLES OF HYPOTHESES IN PUBLISHED ARTICLES

EXAMPLE 1. Working hypothesis (quantitative research)
- A hypothesis that is initially accepted for further research to produce a feasible theory
“As fever may have benefit in shortening the duration of viral illness, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response when taken during the early stages of COVID-19 illness .” 24
“In conclusion, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response . The difference in perceived safety of these agents in COVID-19 illness could be related to the more potent efficacy to reduce fever with ibuprofen compared to acetaminophen. Compelling data on the benefit of fever warrant further research and review to determine when to treat or withhold ibuprofen for early stage fever for COVID-19 and other related viral illnesses .” 24
EXAMPLE 2. Exploratory hypothesis (qualitative research)
- Explores particular areas deeper to clarify subjective experience and develop a formal hypothesis potentially testable in a future quantitative approach
“We hypothesized that when thinking about a past experience of help-seeking, a self distancing prompt would cause increased help-seeking intentions and more favorable help-seeking outcome expectations .” 25
“Conclusion
Although a priori hypotheses were not supported, further research is warranted as results indicate the potential for using self-distancing approaches to increasing help-seeking among some people with depressive symptomatology.” 25
EXAMPLE 3. Hypothesis-generating research to establish a framework for hypothesis testing (qualitative research)
“We hypothesize that compassionate care is beneficial for patients (better outcomes), healthcare systems and payers (lower costs), and healthcare providers (lower burnout). ” 26
Compassionomics is the branch of knowledge and scientific study of the effects of compassionate healthcare. Our main hypotheses are that compassionate healthcare is beneficial for (1) patients, by improving clinical outcomes, (2) healthcare systems and payers, by supporting financial sustainability, and (3) HCPs, by lowering burnout and promoting resilience and well-being. The purpose of this paper is to establish a scientific framework for testing the hypotheses above . If these hypotheses are confirmed through rigorous research, compassionomics will belong in the science of evidence-based medicine, with major implications for all healthcare domains.” 26
EXAMPLE 4. Statistical hypothesis (quantitative research)
- An assumption is made about the relationship among several population characteristics ( gender differences in sociodemographic and clinical characteristics of adults with ADHD ). Validity is tested by statistical experiment or analysis ( chi-square test, Students t-test, and logistic regression analysis)
“Our research investigated gender differences in sociodemographic and clinical characteristics of adults with ADHD in a Japanese clinical sample. Due to unique Japanese cultural ideals and expectations of women's behavior that are in opposition to ADHD symptoms, we hypothesized that women with ADHD experience more difficulties and present more dysfunctions than men . We tested the following hypotheses: first, women with ADHD have more comorbidities than men with ADHD; second, women with ADHD experience more social hardships than men, such as having less full-time employment and being more likely to be divorced.” 27
“Statistical Analysis
( text omitted ) Between-gender comparisons were made using the chi-squared test for categorical variables and Students t-test for continuous variables…( text omitted ). A logistic regression analysis was performed for employment status, marital status, and comorbidity to evaluate the independent effects of gender on these dependent variables.” 27

EXAMPLES OF HYPOTHESIS AS WRITTEN IN PUBLISHED ARTICLES IN RELATION TO OTHER PARTS

EXAMPLE 1. Background, hypotheses, and aims are provided
“Pregnant women need skilled care during pregnancy and childbirth, but that skilled care is often delayed in some countries …( text omitted ). The focused antenatal care (FANC) model of WHO recommends that nurses provide information or counseling to all pregnant women …( text omitted ). Job aids are visual support materials that provide the right kind of information using graphics and words in a simple and yet effective manner. When nurses are not highly trained or have many work details to attend to, these job aids can serve as a content reminder for the nurses and can be used for educating their patients (Jennings, Yebadokpo, Affo, & Agbogbe, 2010) ( text omitted ). Importantly, additional evidence is needed to confirm how job aids can further improve the quality of ANC counseling by health workers in maternal care …( text omitted )” 28
“ This has led us to hypothesize that the quality of ANC counseling would be better if supported by job aids. Consequently, a better quality of ANC counseling is expected to produce higher levels of awareness concerning the danger signs of pregnancy and a more favorable impression of the caring behavior of nurses .” 28
“This study aimed to examine the differences in the responses of pregnant women to a job aid-supported intervention during ANC visit in terms of 1) their understanding of the danger signs of pregnancy and 2) their impression of the caring behaviors of nurses to pregnant women in rural Tanzania.” 28
EXAMPLE 2. Background, hypotheses, and aims are provided
“We conducted a two-arm randomized controlled trial (RCT) to evaluate and compare changes in salivary cortisol and oxytocin levels of first-time pregnant women between experimental and control groups. The women in the experimental group touched and held an infant for 30 min (experimental intervention protocol), whereas those in the control group watched a DVD movie of an infant (control intervention protocol). The primary outcome was salivary cortisol level and the secondary outcome was salivary oxytocin level.” 29
“ We hypothesize that at 30 min after touching and holding an infant, the salivary cortisol level will significantly decrease and the salivary oxytocin level will increase in the experimental group compared with the control group .” 29
EXAMPLE 3. Background, aim, and hypothesis are provided
“In countries where the maternal mortality ratio remains high, antenatal education to increase Birth Preparedness and Complication Readiness (BPCR) is considered one of the top priorities [1]. BPCR includes birth plans during the antenatal period, such as the birthplace, birth attendant, transportation, health facility for complications, expenses, and birth materials, as well as family coordination to achieve such birth plans. In Tanzania, although increasing, only about half of all pregnant women attend an antenatal clinic more than four times [4]. Moreover, the information provided during antenatal care (ANC) is insufficient. In the resource-poor settings, antenatal group education is a potential approach because of the limited time for individual counseling at antenatal clinics.” 30
“This study aimed to evaluate an antenatal group education program among pregnant women and their families with respect to birth-preparedness and maternal and infant outcomes in rural villages of Tanzania.” 30
“ The study hypothesis was if Tanzanian pregnant women and their families received a family-oriented antenatal group education, they would (1) have a higher level of BPCR, (2) attend antenatal clinic four or more times, (3) give birth in a health facility, (4) have less complications of women at birth, and (5) have less complications and deaths of infants than those who did not receive the education .” 30

Research questions and hypotheses are crucial components to any type of research, whether quantitative or qualitative. These questions should be developed at the very beginning of the study. Excellent research questions lead to superior hypotheses, which, like a compass, set the direction of research, and can often determine the successful conduct of the study. Many research studies have floundered because the development of research questions and subsequent hypotheses was not given the thought and meticulous attention needed. The development of research questions and hypotheses is an iterative process based on extensive knowledge of the literature and insightful grasp of the knowledge gap. Focused, concise, and specific research questions provide a strong foundation for constructing hypotheses which serve as formal predictions about the research outcomes. Research questions and hypotheses are crucial elements of research that should not be overlooked. They should be carefully thought of and constructed when planning research. This avoids unethical studies and poor outcomes by defining well-founded objectives that determine the design, course, and outcome of the study.

Disclosure: The authors have no potential conflicts of interest to disclose.

Author Contributions:

Conceptualization: Barroga E, Matanguihan GJ.
Methodology: Barroga E, Matanguihan GJ.
Writing - original draft: Barroga E, Matanguihan GJ.
Writing - review & editing: Barroga E, Matanguihan GJ.

COMMENTS

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PDF Practical Research 1
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