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What Is a Dependent Variable?

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

in a research study what is the dependent variable

Cara Lustik is a fact-checker and copywriter.

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Independent vs. Dependent
Selection Features

Frequently Asked Questions

The dependent variable is the variable that is being measured or tested in an experiment. This is different than the independent variable , which is a variable that stands on its own. For example, in a study looking at how tutoring impacts test scores, the dependent variable would be the participants' test scores since that is what is being measured and the independent variable would be tutoring.

Learn how to tell the difference between dependent and independent variables . We also share how dependent variables are selected in research and a few examples to increase your understanding of how these variables are used in real-life studies.

The dependent variable is called "dependent" because it is thought to depend, in some way, on the variations of the independent variable.

Independent vs. Dependent Variable

In a psychology experiment , researchers study how changes in one variable (the independent variable) change another variable (the dependent variable). Manipulating independent variables and measuring the effect on dependent variables allows researchers to draw conclusions about cause-and-effect relationships.

These experiments can range from simple to quite complicated, so it can sometimes be a bit confusing to know how to identify the independent vs. dependent variables. Here are a couple of questions to ask to help you learn which is which.

Which Variable Is the Experimenter Measuring?

Keep in mind that the dependent variable is the one being measured. So, if the experiment is trying to see how one variable affects another, the variable that is being affected is the dependent variable.

In many psychology experiments and studies, the dependent variable is a measure of a certain aspect of a participant's behavior . In an experiment looking at how sleep affects test performance, for instance, the dependent variable would be test performance.

One way to help identify the dependent variable is to remember that it depends on the independent variable. When researchers make changes to the independent variable, they then measure any changes to the dependent variable.

Which Variable Does the Experimenter Manipulate?

The independent variable is "independent" because the experimenters are free to vary it as they need. This might mean changing the amount, duration, or type of variable that the participants in the study receive as a treatment or condition.

For example, it's common for treatment-based studies to have some subjects receive a certain treatment while others receive no treatment at all (often called a sham or placebo treatment ). In this case, the treatment is an independent variable because it is the one being manipulated or changed.

Variable being manipulated

Doesn't change based on other variables

Stands on its own

Variable being measured

May change based on other variables

Depends on other variables

How to Choose a Dependent Variable

How do researchers determine what will be a good dependent variable? There are a few key features a scientist might consider.

Stability is often a good sign of a higher-quality dependent variable. If the experiment is repeated with the same participants, conditions, and experimental manipulations, the effects on the dependent variable should be very close to what they were the first time around.

A researcher might also choose dependent variables based on the complexity of their study. While some studies only have one dependent variable and one independent variable, it is possible to have several of each type.

Researchers might also want to learn how changes in a single independent variable affect several dependent variables. For example, imagine an experiment where a researcher wants to learn how the messiness of a room influences people's creativity levels .

This research might also want to see how the messiness of a room might influence a person's mood. The messiness of a room would be the independent variable and the study would have two dependent variables: level of creativity and mood.

Ability to Operationalize

Operationalization is defined as "translating a construct into its manifestation." In simple terms, it refers to how a variable will be measured. So, a good dependent variable is one that you are able to measure.

If measuring burnout , for instance, researchers might decide to use the Maslach Burnout Inventory. If measuring depression, they could use the Patient Health Questionnaire-9 (PHQ-9).

Dependent Variable Examples

When learning to identify the dependent variables in an experiment, it can be helpful to look at examples. Here are just a few dependent variable examples in psychology research .

How does the amount of time spent studying influence test scores? The test scores would be the dependent variable and the amount of studying would be the independent variable. The researcher could also change the independent variable by instead evaluating how age or gender influences test scores.
How does stress influence memory? The dependent variable might be scores on a memory test and the independent variable might be exposure to a stressful task.
How does a specific therapeutic technique influence the symptoms of psychological disorders ? In this case, the dependent variable might be defined as the severity of the symptoms a patient is experiencing, while the independent variable would be the use of a specific therapy method .
Does listening to classical music help students perform better on a math exam? The scores on the math exams are the dependent variable and classical music is the independent variable.
How long does it take people to respond to different sounds? The length of time it takes participants to respond to a sound is the dependent variable, while the sounds are the independent variable.
Do first-born children learn to speak at a younger age than second-born children? In this example, the dependent variable is the age at which the child learns to speak and the independent variable is whether the child is first- or second-born.
How does alcohol use influence reaction time while driving? The amount of alcohol a participant ingests is the independent variable, while their performance on the driving test is the dependent variable.

Understanding what a dependent variable is and how it is used can be helpful for interpreting different types of research that you encounter in different settings. When trying to determine which variables are which, remember that the independent variables are the cause while the dependent variables are the effect.

The dependent variable depends on the independent variable. Thus, if the independent variable changes, the dependent variable would likely change too.

The dependent variable is placed on a graph's y-axis. This is the vertical line or the line that extends upward. The independent variable is placed on the graph's x-axis or the horizontal line.

The dependent variable is the one being measured. If looking at how a lack of sleep affects mental health , for instance, mental health is the dependent variable. In a study that seeks to find the effects of supplements on mood , the participants' mood is the dependent variable.

A controlled variable is a variable that doesn't change during the experiment. This enables researchers to assess the relationship between the dependent and independent variables more accurately. For example, if trying to assess the impact of drinking green tea on memory, researchers might ask subjects to drink it at the same time of day. This would be a controlled variable.

U.S. National Library of Medicine. Dependent and independent variables .

Steingrimsdottir HS, Arntzen E. On the utility of within-participant research design when working with patients with neurocognitive disorders . Clin Interv Aging . 2015;10:1189-1199. doi:10.2147/CIA.S81868

Kaliyadan F, Kulkarni V. Types of variables, descriptive statistics, and sample size . Indian Dermatol Online J . 2019;10(1):82-86. doi:10.4103/idoj.IDOJ_468_18

Flannelly LT, Flannelly KJ, Jankowski KR. Independent, dependent, and other variables in healthcare and chaplaincy research . J Health Care Chaplain . 2014;20(4):161-70. doi:10.1080/08854726.2014.959374

Weiten W. Psychology: themes and variations .

Kantowitz BH, Roediger HL, Elmes DG. Experimental psychology .

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By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Educational resources and simple solutions for your research journey

Independent vs Dependent Variables: Definitions & Examples

A variable is an important element of research. It is a characteristic, number, or quantity of any category that can be measured or counted and whose value may change with time or other parameters.

Variables are defined in different ways in different fields. For instance, in mathematics, a variable is an alphabetic character that expresses a numerical value. In algebra, a variable represents an unknown entity, mostly denoted by a, b, c, x, y, z, etc. In statistics, variables represent real-world conditions or factors. Despite the differences in definitions, in all fields, variables represent the entity that changes and help us understand how one factor may or may not influence another factor.

Variables in research and statistics are of different types—independent, dependent, quantitative (discrete or continuous), qualitative (nominal/categorical, ordinal), intervening, moderating, extraneous, confounding, control, and composite. In this article we compare the first two types— independent vs dependent variables .

Table of Contents

What is a variable?

Researchers conduct experiments to understand the cause-and-effect relationships between various entities. In such experiments, the entities whose values change are called variables. These variables describe the relationships among various factors and help in drawing conclusions in experiments. They help in understanding how some factors influence others. Some examples of variables include age, gender, race, income, weight, etc.

As mentioned earlier, different types of variables are used in research. Of these, we will compare the most common types— independent vs dependent variables . The independent variable is the cause and the dependent variable is the effect, that is, independent variables influence dependent variables. In research, a dependent variable is the outcome of interest of the study and the independent variable is the factor that may influence the outcome. Let’s explain this with an independent and dependent variable example : In a study to analyze the effect of antibiotic use on microbial resistance, antibiotic use is the independent variable and microbial resistance is the dependent variable because antibiotic use affects microbial resistance.( 1)

What is an independent variable?

Here is a list of the important characteristics of independent variables .( 2,3)

An independent variable is the factor that is being manipulated in an experiment.
In a research study, independent variables affect or influence dependent variables and cause them to change.
Independent variables help gather evidence and draw conclusions about the research subject.
They’re also called predictors, factors, treatment variables, explanatory variables, and input variables.
On graphs, independent variables are usually placed on the X-axis.
Example: In a study on the relationship between screen time and sleep problems, screen time is the independent variable because it influences sleep (the dependent variable).
In addition, some factors like age are independent variables because other variables such as a person’s income will not change their age.

Types of independent variables

Independent variables in research are of the following two types:( 4)

Quantitative

Quantitative independent variables differ in amounts or scales. They are numeric and answer questions like “how many” or “how often.”

Here are a few quantitative independent variables examples :

Differences in treatment dosages and frequencies: Useful in determining the appropriate dosage to get the desired outcome.
Varying salinities: Useful in determining the range of salinity that organisms can tolerate.

Qualitative

Qualitative independent variables are non-numerical variables.

A few qualitative independent variables examples are listed below:

Different strains of a species: Useful in identifying the strain of a crop that is most resistant to a specific disease.
Varying methods of how a treatment is administered—oral or intravenous.

A quantitative variable is represented by actual amounts and a qualitative variable by categories or groups.

What is a dependent variable ?

Here are a few characteristics of dependent variables: ( 3)

A dependent variable represents a quantity whose value depends on the independent variable and how it is changed.
The dependent variable is influenced by the independent variable under various circumstances.
It is also known as the response variable and outcome variable.
On graphs, dependent variables are placed on the Y-axis.

Here are a few dependent variable examples :

In a study on the effect of exercise on mood, the dependent variable is mood because it may change with exercise.
In a study on the effect of pH on enzyme activity, the enzyme activity is the dependent variable because it changes with changing pH.

Types of dependent variables

Dependent variables are of two types:( 5)

Continuous dependent variables

These variables can take on any value within a given range and are measured on a continuous scale, for example, weight, height, temperature, time, distance, etc.

Categorical or discrete dependent variables

These variables are divided into distinct categories. They are not measured on a continuous scale so only a limited number of values are possible, for example, gender, race, etc.

Differences between independent and dependent variables

The following table compares independent vs dependent variables .

Independent and dependent variable examples

Listed below are a few examples of research questions from various disciplines and their corresponding independent and dependent variables.( 6)

Independent vs dependent variables in research

Experiments usually have at least two variables—independent and dependent. The independent variable is the entity that is being tested and the dependent variable is the result. Classifying independent and dependent variables as discrete and continuous can help in determining the type of analysis that is appropriate in any given research experiment, as shown in the table below. ( 7)

Here are some more research questions and their corresponding independent and dependent variables. ( 6)

How to identify independent vs dependent variables

In addition to all the characteristics of independent and dependent variables listed previously, here are few simple steps to identify the variable types in a research question.( 8)

Keep in mind that there are no specific words that will always describe dependent and independent variables.
If you’re given a paragraph, convert that into a question and identify specific words describing cause and effect.
The word representing the cause is the independent variable and that describing the effect is the dependent variable.

Let’s try out these steps with an example.

A researcher wants to conduct a study to see if his new weight loss medication performs better than two bestseller alternatives. He wants to randomly select 20 subjects from Richmond, Virginia, aged 20 to 30 years and weighing above 60 pounds. Each subject will be randomly assigned to three treatment groups.

To identify the independent and dependent variables, we convert this paragraph into a question, as follows: Does the new medication perform better than the alternatives? Here, the medications are the independent variable and their performances or effect on the individuals are the dependent variable.

Visualizing independent vs dependent variables

Data visualization is the graphical representation of information by using charts, graphs, and maps. Visualizations help in making data more understandable by making it easier to compare elements, identify trends and relationships (among variables), among other functions.

Bar graphs, pie charts, and scatter plots are the best methods to graphically represent variables. While pie charts and bar graphs are suitable for depicting categorical data, scatter plots are appropriate for quantitative data. The independent variable is usually placed on the X-axis and the dependent variable on the Y-axis.

Figure 1 is a scatter plot that depicts the relationship between the number of household members and their monthly grocery expenses. 9 The number of household members is the independent variable and the expenses the dependent variable. The graph shows that as the number of members increases the expenditure also increases.

Key takeaways

Let’s summarize the key takeaways about independent vs dependent variables from this article:

A variable is any entity being measured in a study.
A dependent variable is often the focus of a research study and is the response or outcome. It depends on or varies with changes in other variables.
Independent variables cause changes in dependent variables and don’t depend on other variables.
An independent variable can influence a dependent variable, but a dependent variable cannot influence an independent variable.
An independent variable is the cause and dependent variable is the effect.

Frequently asked questions

What are the different types of variables used in research?

The following table lists the different types of variables used in research.( 10)

2. Why is it important to differentiate between independent vs dependent variables ?

Differentiating between independent vs dependent variables is important to ensure the correct application in your own research and also the correct understanding of other studies. An incorrectly framed research question can lead to confusion and inaccurate results. An easy way to differentiate is to identify the cause and effect.

3. How are independent and dependent variables used in non-experimental research?

So far in this article we talked about variables in relation to experimental research, wherein variables are manipulated or measured to test a hypothesis, that is, to observe the effect on dependent variables. Let’s examine non-experimental research and how variable are used. 11 In non-experimental research, variables are not manipulated but are observed in their natural state. Researchers do not have control over the variables and cannot manipulate them based on their research requirements. For example, a study examining the relationship between income and education level would not manipulate either variable. Instead, the researcher would observe and measure the levels of each variable in the sample population. The level of control researchers have is the major difference between experimental and non-experimental research. Another difference is the causal relationship between the variables. In non-experimental research, it is not possible to establish a causal relationship because other variables may be influencing the outcome.

4. Are there any advantages and disadvantages of using independent vs dependent variables ?

Here are a few advantages and disadvantages of both independent and dependent variables.( 12)

Advantages:

Dependent variables are not liable to any form of bias because they cannot be manipulated by researchers or other external factors.
Independent variables are easily obtainable and don’t require complex mathematical procedures to be observed, like dependent variables. This is because researchers can easily manipulate these variables or collect the data from respondents.
Some independent variables are natural factors and cannot be manipulated. They are also easily obtainable because less time is required for data collection.

Disadvantages:

Obtaining dependent variables is a very expensive and effort- and time-intensive process because these variables are obtained from longitudinal research by solving complex equations.
Independent variables are prone to researcher and respondent bias because they can be manipulated, and this may affect the study results.

We hope this article has provided you with an insight into the use and importance of independent vs dependent variables , which can help you effectively use variables in your next research study.

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Independent and dependent variables: Differences & examples. Statistics by Jim website. Accessed March 10, 2024. https://statisticsbyjim.com/regression/independent-dependent-variables/
Independent variable. Biology online website. Accessed March 9, 2024. https://www.biologyonline.com/dictionary/independent-variable#:~:text=The%20independent%20variable%20in%20research,how%20many%20or%20how%20often .
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Research topics with independent and dependent variables. Good research topics website. Accessed March 12, 2024. https://goodresearchtopics.com/research-topics-with-independent-and-dependent-variables/
Levels of measurement and using the correct statistical test. Univariate quantitative methods. Accessed March 14, 2024. https://web.pdx.edu/~newsomj/uvclass/ho_levels.pdf
Easiest way to identify dependent and independent variables. Afidated website. Accessed March 15, 2024. https://www.afidated.com/2014/07/how-to-identify-dependent-and.html
Choosing data visualizations. Math for the people website. Accessed March 14, 2024. https://web.stevenson.edu/mbranson/m4tp/version1/environmental-racism-choosing-data-visualization.html
Trivedi C. Types of variables in scientific research. Concepts Hacked website. Accessed March 15, 2024. https://conceptshacked.com/variables-in-scientific-research/
Variables in experimental and non-experimental research. Statistics solutions website. Accessed March 14, 2024. https://www.statisticssolutions.com/variables-in-experimental-and-non-experimental-research/#:~:text=The%20independent%20variable%20would%20be,state%20instead%20of%20manipulating%20them .
Dependent vs independent variables: 11 key differences. Formplus website. Accessed March 15, 2024. https://www.formpl.us/blog/dependent-independent-variables

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The Independent Variable vs. Dependent Variable in Research

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In any scientific research, there are typically two variables of interest: independent variables and dependent variables. In forming the backbone of scientific experiments , they help scientists understand relationships, predict outcomes and, in general, make sense of the factors that they're investigating.

Understanding the independent variable vs. dependent variable is so fundamental to scientific research that you need to have a good handle on both if you want to design your own research study or interpret others' findings.

To grasp the distinction between the two, let's delve into their definitions and roles.

What Is an Independent Variable?

What is a dependent variable, research study example, predictor variables vs. outcome variables, other variables, the relationship between independent and dependent variables.

The independent variable, often denoted as X, is the variable that is manipulated or controlled by the researcher intentionally. It's the factor that researchers believe may have a causal effect on the dependent variable.

In simpler terms, the independent variable is the variable you change or vary in an experiment so you can observe its impact on the dependent variable.

The dependent variable, often represented as Y, is the variable that is observed and measured to determine the outcome of the experiment.

In other words, the dependent variable is the variable that is affected by the changes in the independent variable. The values of the dependent variable always depend on the independent variable.

Let's consider an example to illustrate these concepts. Imagine you're conducting a research study aiming to investigate the effect of studying techniques on test scores among students.

In this scenario, the independent variable manipulated would be the studying technique, which you could vary by employing different methods, such as spaced repetition, summarization or practice testing.

The dependent variable, in this case, would be the test scores of the students. As the researcher following the scientific method , you would manipulate the independent variable (the studying technique) and then measure its impact on the dependent variable (the test scores).

You can also categorize variables as predictor variables or outcome variables. Sometimes a researcher will refer to the independent variable as the predictor variable since they use it to predict or explain changes in the dependent variable, which is also known as the outcome variable.

When conducting an experiment or study, it's crucial to acknowledge the presence of other variables, or extraneous variables, which may influence the outcome of the experiment but are not the focus of study.

These variables can potentially confound the results if they aren't controlled. In the example from above, other variables might include the students' prior knowledge, level of motivation, time spent studying and preferred learning style.

As a researcher, it would be your goal to control these extraneous variables to ensure you can attribute any observed differences in the dependent variable to changes in the independent variable. In practice, however, it's not always possible to control every variable.

The distinction between independent and dependent variables is essential for designing and conducting research studies and experiments effectively.

By manipulating the independent variable and measuring its impact on the dependent variable while controlling for other factors, researchers can gain insights into the factors that influence outcomes in their respective fields.

Whether investigating the effects of a new drug on blood pressure or studying the relationship between socioeconomic factors and academic performance, understanding the role of independent and dependent variables is essential for advancing knowledge and making informed decisions.

Correlation vs. Causation

Understanding the relationship between independent and dependent variables is essential for making sense of research findings. Depending on the nature of this relationship, researchers may identify correlations or infer causation between the variables.

Correlation implies that changes in one variable are associated with changes in another variable, while causation suggests that changes in the independent variable directly cause changes in the dependent variable.

Control and Intervention

In experimental research, the researcher has control over the independent variable, allowing them to manipulate it to observe its effects on the dependent variable. This controlled manipulation distinguishes experiments from other types of research designs.

For example, in observational studies, researchers merely observe variables without intervention, meaning they don't control or manipulate any variables.

Context and Analysis

Whether it's intentional or unintentional, independent, dependent and other variables can vary in different contexts, and their effects may differ based on various factors, such as age, characteristics of the participants, environmental influences and so on.

Researchers employ statistical analysis techniques to measure and analyze the relationships between these variables, helping them to draw meaningful conclusions from their data.

We created this article in conjunction with AI technology, then made sure it was fact-checked and edited by a HowStuffWorks editor.

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