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- Independent vs. Dependent Variables | Definition & Examples
Independent vs. Dependent Variables | Definition & Examples
Published on February 3, 2022 by Pritha Bhandari . Revised on June 22, 2023.
In research, variables are any characteristics that can take on different values, such as height, age, temperature, or test scores.
Researchers often manipulate or measure independent and dependent variables in studies to test cause-and-effect relationships.
- The independent variable is the cause. Its value is independent of other variables in your study.
- The dependent variable is the effect. Its value depends on changes in the independent variable.
Your independent variable is the temperature of the room. You vary the room temperature by making it cooler for half the participants, and warmer for the other half.
Table of contents
What is an independent variable, types of independent variables, what is a dependent variable, identifying independent vs. dependent variables, independent and dependent variables in research, visualizing independent and dependent variables, other interesting articles, frequently asked questions about independent and dependent variables.
An independent variable is the variable you manipulate or vary in an experimental study to explore its effects. It’s called “independent” because it’s not influenced by any other variables in the study.
Independent variables are also called:
- Explanatory variables (they explain an event or outcome)
- Predictor variables (they can be used to predict the value of a dependent variable)
- Right-hand-side variables (they appear on the right-hand side of a regression equation).
These terms are especially used in statistics , where you estimate the extent to which an independent variable change can explain or predict changes in the dependent variable.
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There are two main types of independent variables.
- Experimental independent variables can be directly manipulated by researchers.
- Subject variables cannot be manipulated by researchers, but they can be used to group research subjects categorically.
In experiments, you manipulate independent variables directly to see how they affect your dependent variable. The independent variable is usually applied at different levels to see how the outcomes differ.
You can apply just two levels in order to find out if an independent variable has an effect at all.
You can also apply multiple levels to find out how the independent variable affects the dependent variable.
You have three independent variable levels, and each group gets a different level of treatment.
You randomly assign your patients to one of the three groups:
- A low-dose experimental group
- A high-dose experimental group
- A placebo group (to research a possible placebo effect )
A true experiment requires you to randomly assign different levels of an independent variable to your participants.
Random assignment helps you control participant characteristics, so that they don’t affect your experimental results. This helps you to have confidence that your dependent variable results come solely from the independent variable manipulation.
Subject variables are characteristics that vary across participants, and they can’t be manipulated by researchers. For example, gender identity, ethnicity, race, income, and education are all important subject variables that social researchers treat as independent variables.
It’s not possible to randomly assign these to participants, since these are characteristics of already existing groups. Instead, you can create a research design where you compare the outcomes of groups of participants with characteristics. This is a quasi-experimental design because there’s no random assignment. Note that any research methods that use non-random assignment are at risk for research biases like selection bias and sampling bias .
Your independent variable is a subject variable, namely the gender identity of the participants. You have three groups: men, women and other.
Your dependent variable is the brain activity response to hearing infant cries. You record brain activity with fMRI scans when participants hear infant cries without their awareness.
A dependent variable is the variable that changes as a result of the independent variable manipulation. It’s the outcome you’re interested in measuring, and it “depends” on your independent variable.
In statistics , dependent variables are also called:
- Response variables (they respond to a change in another variable)
- Outcome variables (they represent the outcome you want to measure)
- Left-hand-side variables (they appear on the left-hand side of a regression equation)
The dependent variable is what you record after you’ve manipulated the independent variable. You use this measurement data to check whether and to what extent your independent variable influences the dependent variable by conducting statistical analyses.
Based on your findings, you can estimate the degree to which your independent variable variation drives changes in your dependent variable. You can also predict how much your dependent variable will change as a result of variation in the independent variable.
Distinguishing between independent and dependent variables can be tricky when designing a complex study or reading an academic research paper .
A dependent variable from one study can be the independent variable in another study, so it’s important to pay attention to research design .
Here are some tips for identifying each variable type.
Recognizing independent variables
Use this list of questions to check whether you’re dealing with an independent variable:
- Is the variable manipulated, controlled, or used as a subject grouping method by the researcher?
- Does this variable come before the other variable in time?
- Is the researcher trying to understand whether or how this variable affects another variable?
Recognizing dependent variables
Check whether you’re dealing with a dependent variable:
- Is this variable measured as an outcome of the study?
- Is this variable dependent on another variable in the study?
- Does this variable get measured only after other variables are altered?
Independent and dependent variables are generally used in experimental and quasi-experimental research.
Here are some examples of research questions and corresponding independent and dependent variables.
For experimental data, you analyze your results by generating descriptive statistics and visualizing your findings. Then, you select an appropriate statistical test to test your hypothesis .
The type of test is determined by:
- your variable types
- level of measurement
- number of independent variable levels.
You’ll often use t tests or ANOVAs to analyze your data and answer your research questions.
In quantitative research , it’s good practice to use charts or graphs to visualize the results of studies. Generally, the independent variable goes on the x -axis (horizontal) and the dependent variable on the y -axis (vertical).
The type of visualization you use depends on the variable types in your research questions:
- A bar chart is ideal when you have a categorical independent variable.
- A scatter plot or line graph is best when your independent and dependent variables are both quantitative.
To inspect your data, you place your independent variable of treatment level on the x -axis and the dependent variable of blood pressure on the y -axis.
You plot bars for each treatment group before and after the treatment to show the difference in blood pressure.
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.
- Normal distribution
- Degrees of freedom
- Null hypothesis
- Discourse analysis
- Control groups
- Mixed methods research
- Non-probability sampling
- Quantitative research
- Ecological validity
- Rosenthal effect
- Implicit bias
- Cognitive bias
- Selection bias
- Negativity bias
- Status quo bias
An independent variable is the variable you manipulate, control, or vary in an experimental study to explore its effects. It’s called “independent” because it’s not influenced by any other variables in the study.
A dependent variable is what changes as a result of the independent variable manipulation in experiments . It’s what you’re interested in measuring, and it “depends” on your independent variable.
In statistics, dependent variables are also called:
Determining cause and effect is one of the most important parts of scientific research. It’s essential to know which is the cause – the independent variable – and which is the effect – the dependent variable.
You want to find out how blood sugar levels are affected by drinking diet soda and regular soda, so you conduct an experiment .
- The type of soda – diet or regular – is the independent variable .
- The level of blood sugar that you measure is the dependent variable – it changes depending on the type of soda.
No. The value of a dependent variable depends on an independent variable, so a variable cannot be both independent and dependent at the same time. It must be either the cause or the effect, not both!
Yes, but including more than one of either type requires multiple research questions .
For example, if you are interested in the effect of a diet on health, you can use multiple measures of health: blood sugar, blood pressure, weight, pulse, and many more. Each of these is its own dependent variable with its own research question.
You could also choose to look at the effect of exercise levels as well as diet, or even the additional effect of the two combined. Each of these is a separate independent variable .
To ensure the internal validity of an experiment , you should only change one independent variable at a time.
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What Are Independent and Dependent Variables?
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Both the independent variable and dependent variable are examined in an experiment using the scientific method , so it's important to know what they are and how to use them. Here are the definitions for independent and dependent variables, examples of each variable, and the explanation for how to graph them.
The independent variable is the condition that you change in an experiment. It is the variable you control. It is called independent because its value does not depend on and is not affected by the state of any other variable in the experiment. Sometimes you may hear this variable called the "controlled variable" because it is the one that is changed. Do not confuse it with a "control variable," which is a variable that is purposely held constant so that it can't affect the outcome of the experiment.
The dependent variable is the condition that you measure in an experiment. You are assessing how it responds to a change in the independent variable, so you can think of it as depending on the independent variable. Sometimes the dependent variable is called the "responding variable."
Independent and Dependent Variable Examples
- In a study to determine whether how long a student sleeps affects test scores, the independent variable is the length of time spent sleeping while the dependent variable is the test score.
- You want to compare brands of paper towels, to see which holds the most liquid. The independent variable in your experiment would be the brand of paper towel. The dependent variable would be the amount of liquid absorbed by the paper towel.
- In an experiment to determine how far people can see into the infrared part of the spectrum, the wavelength of light is the independent variable and whether the light is observed (the response) is the dependent variable.
- If you want to know whether caffeine affects your appetite, the presence/absence of a given amount of caffeine would be the independent variable. How hungry you are would be the dependent variable.
- You want to determine whether a chemical is essential for rat nutrition, so you design an experiment. The presence/absence of the chemical is the independent variable. The health of the rat (whether it lives and can reproduce) is the dependent variable. If you determine the substance is necessary for proper nutrition, a follow-up experiment might determine how much of the chemical is needed. Here, the amount of chemical would be the independent variable and the rat health would be the dependent variable.
How to Tell the Independent and Dependent Variable Apart
If you are having a hard time identifying which variable is the independent variable and which is the dependent variable, remember the dependent variable is the one affected by a change in the independent variable. If you write out the variables in a sentence that shows cause and effect, the independent variable causes the effect on the dependent variable. If you have the variables in the wrong order, the sentence won't make sense.
Independent variable causes an effect on the dependent variable.
Example : How long you sleep (independent variable) affects your test score (dependent variable).
This makes sense, but:
Example : Your test score affects how long you sleep.
This doesn't really make sense (unless you can't sleep because you are worried you failed a test, but that would be a different experiment).
How to Plot Variables on a Graph
There is a standard method for graphing the independent and dependent variable. The x-axis is the independent variable, while the y-axis is the dependent variable. You can use the DRY MIX acronym to help remember how to graph variables:
D = dependent variable R = responding variable Y = graph on the vertical or y-axis
M = manipulated variable I = independent variable X = graph on the horizontal or x-axis
Test your understanding with the scientific method quiz .
- Dependent Variable Definition and Examples
- Scientific Variable
- What Is an Experiment? Definition and Design
- Six Steps of the Scientific Method
- The Significance of Negative Slope
- Difference Between Independent and Dependent Variables
- The Differences Between Explanatory and Response Variables
- What Is a Hypothesis? (Science)
- Scientific Method Flow Chart
- Scientific Method Vocabulary Terms
- How To Design a Science Fair Experiment
- What Are the Elements of a Good Hypothesis?
- How to Write a Lab Report
- What Is a Bar Graph?
- Understanding Simple vs Controlled Experiments
- Independent Variable Definition and Examples
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Understanding the Role of Independent and Dependent Variables
- August 26, 2021
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A variable in the field of research is an object, idea, or any other characteristic which can take any value that you are trying to measure. A variable can be age, blood pressure, height, exam score, sea level, time, etc.
There are primarily two types of variables used in an experiment – Independent Variables and Dependent Variables.
Independent Variable Definition:
As per the name, an independent variable (IV) stands alone. The value does not change due to the impact of any other variable. The researcher manipulates or changes the independent variable to measure its impact on other variables.
Independent variables, in some cases, can already exist, like age, but it is not dependent on any other variable . The variable plays a significant role in research by assisting you in examining causal relationships and testing hypotheses. By manipulating this variable, you can determine its impact on DV and establish a cause-and-effect relationship.
Dependent Variables Definition:
Similarly, a dependent variable (DV) as the name suggests, depends on other variables. It is the variable that is being tested in the experiment. A researcher measures the outcome of the experiment to see how other variables cause changes in the value of a dependent variable.
The causal relationship between dependent & independent variables in research studies helps you assess the effects, associations, and correlations.
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How to identify independent and dependent variables.
The IV is the variable you can manipulate or control in research. You can deliberately change is to observe its impact on the dependent variable. Whereas DV is the variable you observe/ analyze. You examine the changes in the dependent variable in response to the changes in the independent variable.
The most common independent and dependent variable identifier is:
“Which variable is being intentionally manipulated?”. This question can help you identify the independent variable.
“ What is the response being observed?” This will help you identify the dependent variable.
Let’s use “Test Scores” as an example of independent and dependent variables in research studies.
You want to see the effect of studying or sleeping on a test score . In the example, “test score” is the dependent variable. “Studying” or “sleeping” is the independent variable because these factors impact how much a student scores on the test.
So, in the experiment, you are trying to determine if and how one variable affects the other. Here you can manipulate the independent variable (time of studying) to see if the dependent variable (test score) changes or not.
Another independent and dependent variable identifier is the characteristics of both variables.
Characteristics of independent variables:
IV possesses the following characteristics as the presumed causes of the outcome you investigate in the research.
- Manipulative – You can control the variable and change its value or condition.
- Variability – The variable has a different value that you can assign.
- Exogenity – Other variables cannot influence an IV, which makes it external to the research subject.
Characteristics of dependent variables:
DV possesses the following characteristics as the outcomes that researchers observe to assess the impact of IV.
- Response – DV is the variable that responds to the manipulation in an IV.
- Measurability – You can quantity or measure a dependent variable.
- Outcome – The variable represents the result of the IV.
These two methods are some commonly used independent and dependent variable identifiers.
Difference between Independent and Dependent Variable
The easiest way to identify which variable in your experiment is the Independent Variable (IV) and which one is the Dependent Variable (DV) is by putting both variables in the sentence below in a way that makes sense.
“The IV causes a change in the DV. It is not possible that DV could cause any change in IV.”
In an experiment, when you make changes in the Independent Variables, your aim is to measure the changes it causes to the Dependent Variables.
Remember that the dependent variable is affected by the changes you make in the independent variable.
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Examples of Independent and Dependent Variables
Let’s explore some examples of dependent and independent variables to understand their properties better.
- How does the amount of sleep impact test scores?
- Independent Variable: Time spent on sleeping before the exam
- Dependent Variable: Test Score
- What is the effect of fast food on blood pressure?
- Independent Variable : Consumption of fast food
- Dependent Variable: Blood Pressure
- What is the effect of caffeine on sleep?
- Independent Variable: the amount of caffeine consumed
- Dependent Variable: Sleep
Here are more examples of independent and dependent variables in research studies in various fields.
1. Social science surveys:
In social science research, you can use IV and DV to understand and assess various aspects of human behavior, social phenomena, etc.
Here are some IV and DV examples in social surveys.
- Assessing the relationship between income level (independent variable) and lifestyle (dependent variable).
- Observing the level of social aggression (dependent variable) in response to various media violence (independent variable).
2. Healthcare surveys:
In medical/healthcare research, you can use IV and DV to evaluate the effectiveness of medical interventions and treatments.
Here are some IV and DV examples in medical surveys.
- Testing the impact of a new medication (independent variable) on reducing migraine (dependent variable) in a clinical trial.
- Measuring blood pressure (dependent variable) before and after administering a new medication (independent variable) .
3. Market research:
In the field of MR, you can use IV and DV to study consumer behavior and market trends.
Here are some IV and DV examples in market research.
- Analyzing the impact of new packaging (independent variable) on the sales volume (dependent variable) of the product.
B. Examining consumer perception (dependent variable) in response to the change in price (independent variable) of the product.
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In Experiment – Independent Vs. Dependent Variables Examples
In an Experiment, the independent variable is the characteristic manipulated by the researcher to gauge the effect of the changes on the dependent variable.
Note that the resulting change in the dependent variable is always measured by altering the independent variable.
Here we will look into several dependent and independent variables in research examples.
IV and DV examples 1: Assessing the impact of exposure to classical music on math scores.
You want to determine the effect of exposure to classical music on the test scores on math.
To see the changes in the test score, divide students into two groups.
- Students in Group A listened to classical music for an hour every day for two months.
- Students in Group B were not instructed to listen to classical music.
After two months, students of both groups were given a math test. It was seen that Group A performed better than Group B.
In the experiment, test score in math exam was the dependent variable, and the exposure or lack thereof to classical music was the independent variable.
In an Experiment, while the most common study has one independent variable and one dependent variable, it is also possible to have a different level of each variable.
- As a researcher, you may want to learn how a single Independent Variable can impact two different dependent variables.
IV and DV example 2: Investing the impact of video games on teenagers’ memory and mood.
For example, you run an experiment to learn how playing video games impacts a teenager’s memory as well as their mood. In the experiment, while playing video games is your independent variable, the teenager’s memory and mood are your two dependent variables.
- Similarly, independent variables can have different levels. In some experiments, you may need to use multiple independent variables to see the various effects it may have on the single dependent variable .
IV and DV example 3: Observing the effect of a healthy diet on weight loss.
For example, you want to see how a healthy diet can help with weight loss. So, you will look for several types of a healthy diet and their impact on weight. In this case, different types of diet would be your different levels of the independent variable, while weight loss is the outcome that makes it the dependent variable.
- Applying two levels of IV can tell you if it affects the DV.
- Applying multiple levels of IV can show you how it influences the outcome of DV.
- In some cases of experimental research, it is not possible to change the independent variable.
IV and DV example 4: Assessing the impact of age on weight gain.
In this example, you want to observe if there is any cause-and-effect relationship between age and weight gain.
- Age is your Independent Variable
- Weight gain is your Dependent Variable
The dependent and independent variables in this research example differ slightly. Here, you cannot control the age of the people you are studying to understand its impact on weight gain.
So, you compare the factors that had an effect on weight and the factors that did not. Comparing the difference in the other factors, you can learn the changes in a person’s weight caused by their age.
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Pitfalls to Be Aware Of
Aside from dependent and independent variables, you must be aware of other variables that may influence the result of your experiment.
Extraneous Variables : may influence the relationships between the Independent and the Dependent Variable. Researchers try to identify these variables in order to control them.
Confounding Variables : are those variables that cannot be controlled in research. In non-experimental research, there may be other variables that you have not identified. These variables may be influencing changes in the outcome.
In this blog, we have shared many examples of independent and dependent variables in research studies and highlighted their characteristics.
Understanding independent and dependent variables is significant in research as it ensures the validity and reliability of the research. The two variables help you establish cause-and-effect relationships and draw meaningful conclusions.
In the blog, we have also mentioned the independent and dependent variable identifiers so you can delve deeper into the world of research.
The main difference between Independent & Dependent Variables is in the definition.
- IV in research can be manipulated or altered to see their impact on other variables.
- The DV is dependent on other variables. It is the variable that is measured or tested by a researcher.
The best way to identify dependent and independent variables in research is by putting the variables in the sentence “ The Independent Variables cause a change in Dependent Variable ”.
Variables are characteristics that take on different values. In experimental research, there are three types of Variables: Independent, Dependent, and Controlled Variables.
When you try to boil a potato, as the temperature of water rises the potato boils faster. Here, the temperature of the water is an Independent Variable and Potato is the Dependent Variable.
An independent variable is often denoted by “ x .” It is a variable whose value does not depend on another variable.
An independent variable is the factors or conditions that you can manipulate in an experiment. This variable can directly affect the value of a dependent variable.
A Dependent variable is denoted by “ y.” It is a variable whose value depends on that of an independent variable.
In an experiment, a dependent variable is a factor that is observed or measured. When you vary an independent variable, you observe the change in your dependent variable.
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15 Independent and Dependent Variable Examples
An independent variable (IV) is what is manipulated in a scientific experiment to determine its effect on the dependent variable (DV).
By varying the level of the independent variable and observing associated changes in the dependent variable, a researcher can conclude whether the independent variable affects the dependent variable or not.
This can provide very valuable information when studying just about any subject.
Because the researcher controls the level of the independent variable, it can be determined if the independent variable has a causal effect on the dependent variable.
The term causation is vitally important. Scientists want to know what causes changes in the dependent variable. The only way to do that is to manipulate the independent variable and observe any changes in the dependent variable.
Definition of Independent and Dependent Variables
The independent variable and dependent variable are used in a very specific type of scientific study called the experiment .
Although there are many variations of the experiment, generally speaking, it involves either the presence or absence of the independent variable and the observation of what happens to the dependent variable.
The research participants are randomly assigned to either receive the independent variable (called the treatment condition), or not receive the independent variable (called the control condition).
Other variations of an experiment might include having multiple levels of the independent variable.
If the independent variable affects the dependent variable, then it should be possible to observe changes in the dependent variable based on the presence or absence of the independent variable.
Of course, there are a lot of issues to consider when conducting an experiment, but these are the basic principles.
These concepts should not be confused with predictor and outcome variables .
Examples of Independent and Dependent Variables
1. gatorade and improved athletic performance.
A sports medicine researcher has been hired by Gatorade to test the effects of its sports drink on athletic performance. The company wants to claim that when an athlete drinks Gatorade, their performance will improve.
If they can back up that claim with hard scientific data, that would be great for sales.
So, the researcher goes to a nearby university and randomly selects both male and female athletes from several sports: track and field, volleyball, basketball, and football. Each athlete will run on a treadmill for one hour while their heart rate is tracked.
All of the athletes are given the exact same amount of liquid to consume 30-minutes before and during their run. Half are given Gatorade, and the other half are given water, but no one knows what they are given because both liquids have been colored.
In this example, the independent variable is Gatorade, and the dependent variable is heart rate.
2. Chemotherapy and Cancer
A hospital is investigating the effectiveness of a new type of chemotherapy on cancer. The researchers identified 120 patients with relatively similar types of cancerous tumors in both size and stage of progression.
The patients are randomly assigned to one of three groups: one group receives no chemotherapy, one group receives a low dose of chemotherapy, and one group receives a high dose of chemotherapy.
Each group receives chemotherapy treatment three times a week for two months, except for the no-treatment group. At the end of two months, the doctors measure the size of each patient’s tumor.
In this study, despite the ethical issues (remember this is just a hypothetical example), the independent variable is chemotherapy, and the dependent variable is tumor size.
3. Interior Design Color and Eating Rate
A well-known fast-food corporation wants to know if the color of the interior of their restaurants will affect how fast people eat. Of course, they would prefer that consumers enter and exit quickly to increase sales volume and profit.
So, they rent space in a large shopping mall and create three different simulated restaurant interiors of different colors. One room is painted mostly white with red trim and seats; one room is painted mostly white with blue trim and seats; and one room is painted mostly white with off-white trim and seats.
Next, they randomly select shoppers on Saturdays and Sundays to eat for free in one of the three rooms. Each shopper is given a box of the same food and drink items and sent to one of the rooms. The researchers record how much time elapses from the moment they enter the room to the moment they leave.
The independent variable is the color of the room, and the dependent variable is the amount of time spent in the room eating.
4. Hair Color and Attraction
A large multinational cosmetics company wants to know if the color of a woman’s hair affects the level of perceived attractiveness in males. So, they use Photoshop to manipulate the same image of a female by altering the color of her hair: blonde, brunette, red, and brown.
Next, they randomly select university males to enter their testing facilities. Each participant sits in front of a computer screen and responds to questions on a survey. At the end of the survey, the screen shows one of the photos of the female.
At the same time, software on the computer that utilizes the computer’s camera is measuring each male’s pupil dilation. The researchers believe that larger dilation indicates greater perceived attractiveness.
The independent variable is hair color, and the dependent variable is pupil dilation.
5. Mozart and Math
After many claims that listening to Mozart will make you smarter, a group of education specialists decides to put it to the test. So, first, they go to a nearby school in a middle-class neighborhood.
During the first three months of the academic year, they randomly select some 5th-grade classrooms to listen to Mozart during their lessons and exams. Other 5 th grade classrooms will not listen to any music during their lessons and exams.
The researchers then compare the scores of the exams between the two groups of classrooms.
Although there are a lot of obvious limitations to this hypothetical, it is the first step.
The independent variable is Mozart, and the dependent variable is exam scores.
6. Essential Oils and Sleep
A company that specializes in essential oils wants to examine the effects of lavender on sleep quality. They hire a sleep research lab to conduct the study. The researchers at the lab have their usual test volunteers sleep in individual rooms every night for one week.
The conditions of each room are all exactly the same, except that half of the rooms have lavender released into the rooms and half do not. While the study participants are sleeping, their heart rates and amount of time spent in deep sleep are recorded with high-tech equipment.
At the end of the study, the researchers compare the total amount of time spent in deep sleep of the lavender-room participants with the no lavender-room participants.
The independent variable in this sleep study is lavender, and the dependent variable is the total amount of time spent in deep sleep.
7. Teaching Style and Learning
A group of teachers is interested in which teaching method will work best for developing critical thinking skills.
So, they train a group of teachers in three different teaching styles : teacher-centered, where the teacher tells the students all about critical thinking; student-centered, where the students practice critical thinking and receive teacher feedback; and AI-assisted teaching, where the teacher uses a special software program to teach critical thinking.
At the end of three months, all the students take the same test that assesses critical thinking skills. The teachers then compare the scores of each of the three groups of students.
The independent variable is the teaching method, and the dependent variable is performance on the critical thinking test.
8. Concrete Mix and Bridge Strength
A chemicals company has developed three different versions of their concrete mix. Each version contains a different blend of specially developed chemicals. The company wants to know which version is the strongest.
So, they create three bridge molds that are identical in every way. They fill each mold with one of the different concrete mixtures. Next, they test the strength of each bridge by placing progressively more weight on its center until the bridge collapses.
In this study, the independent variable is the concrete mixture, and the dependent variable is the amount of weight at collapse.
9. Recipe and Consumer Preferences
People in the pizza business know that the crust is key. Many companies, large and small, will keep their recipe a top secret. Before rolling out a new type of crust, the company decides to conduct some research on consumer preferences.
The company has prepared three versions of their crust that vary in crunchiness, they are: a little crunchy, very crunchy, and super crunchy. They already have a pool of consumers that fit their customer profile and they often use them for testing.
Each participant sits in a booth and takes a bite of one version of the crust. They then indicate how much they liked it by pressing one of 5 buttons: didn’t like at all, liked, somewhat liked, liked very much, loved it.
The independent variable is the level of crust crunchiness, and the dependent variable is how much it was liked.
10. Protein Supplements and Muscle Mass
A large food company is considering entering the health and nutrition sector. Their R&D food scientists have developed a protein supplement that is designed to help build muscle mass for people that work out regularly.
The company approaches several gyms near its headquarters. They enlist the cooperation of over 120 gym rats that work out 5 days a week. Their muscle mass is measured, and only those with a lower level are selected for the study, leaving a total of 80 study participants.
They randomly assign half of the participants to take the recommended dosage of their supplement every day for three months after each workout. The other half takes the same amount of something that looks the same but actually does nothing to the body.
At the end of three months, the muscle mass of all participants is measured.
The independent variable is the supplement, and the dependent variable is muscle mass.
11. Air Bags and Skull Fractures
In the early days of airbags , automobile companies conducted a great deal of testing. At first, many people in the industry didn’t think airbags would be effective at all. Fortunately, there was a way to test this theory objectively.
In a representative example: Several crash cars were outfitted with an airbag, and an equal number were not. All crash cars were of the same make, year, and model. Then the crash experts rammed each car into a crash wall at the same speed. Sensors on the crash dummy skulls allowed for a scientific analysis of how much damage a human skull would incur.
The amount of skull damage of dummies in cars with airbags was then compared with those without airbags.
The independent variable was the airbag and the dependent variable was the amount of skull damage.
12. Vitamins and Health
Some people take vitamins every day. A group of health scientists decides to conduct a study to determine if taking vitamins improves health.
They randomly select 1,000 people that are relatively similar in terms of their physical health. The key word here is “similar.”
Because the scientists have an unlimited budget (and because this is a hypothetical example, all of the participants have the same meals delivered to their homes (breakfast, lunch, and dinner), every day for one year.
In addition, the scientists randomly assign half of the participants to take a set of vitamins, supplied by the researchers every day for 1 year. The other half do not take the vitamins.
At the end of one year, the health of all participants is assessed, using blood pressure and cholesterol level as the key measurements.
In this highly unrealistic study, the independent variable is vitamins, and the dependent variable is health, as measured by blood pressure and cholesterol levels.
13. Meditation and Stress
Does practicing meditation reduce stress? If you have ever wondered if this is true or not, then you are in luck because there is a way to know one way or the other.
All we have to do is find 90 people that are similar in age, stress levels, diet and exercise, and as many other factors as we can think of.
Next, we randomly assign each person to either practice meditation every day, three days a week, or not at all. After three months, we measure the stress levels of each person and compare the groups.
How should we measure stress? Well, there are a lot of ways. We could measure blood pressure, or the amount of the stress hormone cortisol in their blood, or by using a paper and pencil measure such as a questionnaire that asks them how much stress they feel.
In this study, the independent variable is meditation and the dependent variable is the amount of stress (however it is measured).
14. Video Games and Aggression
When video games started to become increasingly graphic, it was a huge concern in many countries in the world. Educators, social scientists, and parents were shocked at how graphic games were becoming.
Since then, there have been hundreds of studies conducted by psychologists and other researchers. A lot of those studies used an experimental design that involved males of various ages randomly assigned to play a graphic or non-graphic video game.
Afterward, their level of aggression was measured via a wide range of methods, including direct observations of their behavior, their actions when given the opportunity to be aggressive, or a variety of other measures.
So many studies have used so many different ways of measuring aggression.
In these experimental studies, the independent variable was graphic video games, and the dependent variable was observed level of aggression.
15. Vehicle Exhaust and Cognitive Performance
Car pollution is a concern for a lot of reasons. In addition to being bad for the environment, car exhaust may cause damage to the brain and impair cognitive performance.
One way to examine this possibility would be to conduct an animal study. The research would look something like this: laboratory rats would be raised in three different rooms that varied in the degree of car exhaust circulating in the room: no exhaust, little exhaust, or a lot of exhaust.
After a certain period of time, perhaps several months, the effects on cognitive performance could be measured.
One common way of assessing cognitive performance in laboratory rats is by measuring the amount of time it takes to run a maze successfully. It would also be possible to examine the physical effects of car exhaust on the brain by conducting an autopsy.
In this animal study, the independent variable would be car exhaust and the dependent variable would be amount of time to run a maze.
Read Next: Extraneous Variables Examples
The experiment is an incredibly valuable way to answer scientific questions regarding the cause and effect of certain variables. By manipulating the level of an independent variable and observing corresponding changes in a dependent variable, scientists can gain an understanding of many phenomena.
For example, scientists can learn if graphic video games make people more aggressive, if mediation reduces stress, if Gatorade improves athletic performance, and even if certain medical treatments can cure cancer.
The determination of causality is the key benefit of manipulating the independent variable and them observing changes in the dependent variable. Other research methodologies can reveal factors that are related to the dependent variable or associated with the dependent variable, but only when the independent variable is controlled by the researcher can causality be determined.
Ferguson, C. J. (2010). Blazing Angels or Resident Evil? Can graphic video games be a force for good? Review of General Psychology, 14 (2), 68-81. https://doi.org/10.1037/a0018941
Flannelly, L. T., Flannelly, K. J., & Jankowski, K. R. (2014). Independent, dependent, and other variables in healthcare and chaplaincy research. Journal of Health Care Chaplaincy , 20 (4), 161–170. https://doi.org/10.1080/08854726.2014.959374
Manocha, R., Black, D., Sarris, J., & Stough, C.(2011). A randomized, controlled trial of meditation for work stress, anxiety and depressed mood in full-time workers. Evidence-Based Complementary and Alternative Medicine , vol. 2011, Article ID 960583. https://doi.org/10.1155/2011/960583
Rumrill, P. D., Jr. (2004). Non-manipulation quantitative designs. Work (Reading, Mass.) , 22 (3), 255–260.
Taylor, J. M., & Rowe, B. J. (2012). The “Mozart Effect” and the mathematical connection, Journal of College Reading and Learning, 42 (2), 51-66. https://doi.org/10.1080/10790195.2012.10850354
Dave Cornell (PhD)
Dr. Cornell has worked in education for more than 20 years. His work has involved designing teacher certification for Trinity College in London and in-service training for state governments in the United States. He has trained kindergarten teachers in 8 countries and helped businessmen and women open baby centers and kindergartens in 3 countries.
- Dave Cornell (PhD) #molongui-disabled-link 25 Positive Punishment Examples
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Chris Drew (PhD)
This article was peer-reviewed and edited by Chris Drew (PhD). The review process on Helpful Professor involves having a PhD level expert fact check, edit, and contribute to articles. Reviewers ensure all content reflects expert academic consensus and is backed up with reference to academic studies. Dr. Drew has published over 20 academic articles in scholarly journals. He is the former editor of the Journal of Learning Development in Higher Education and holds a PhD in Education from ACU.
- Chris Drew (PhD) #molongui-disabled-link 25 Positive Punishment Examples
- Chris Drew (PhD) #molongui-disabled-link 25 Dissociation Examples (Psychology)
- Chris Drew (PhD) #molongui-disabled-link 15 Zone of Proximal Development Examples
- Chris Drew (PhD) #molongui-disabled-link Perception Checking: 15 Examples and Definition
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Independent vs. Dependent Variables – Use & Examples
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Understanding independent vs. dependent variables of experimental design, statistical modelling, and hypothesis testing in various disciplines shapes a bedrock of methodology . An independent variable is the factor manipulated to observe its effect, whereas a dependent variable is the outcome or response that is measured. In essence, the independent variable causes a change, and the dependent variable is what is being affected. Distinguishing between independent and dependent variables is vital for organizing experiments, interpreting results, and drawing meaningful conclusions. Learn more in this article.
- 1 Independent vs. Dependent Variables – In a Nutshell
- 2 Definition: Independent vs. dependent variables
- 3 Independent vs. dependent variables in research
- 4 Detecting independent vs. dependent variables
- 5 Illustrating independent vs. dependent variables
Independent vs. Dependent Variables – In a Nutshell
- An independent variable is one that is manipulated by the researcher.
- A dependent variable is one that is being tested in a research experiment.
- Scientific research assesses the effect on dependent variables based on the changes in independent variables.
- This article shows examples of how to illustrate dependent and independent variables in graphs.
Definition: Independent vs. dependent variables
To distinguish independent vs. dependent variables, it is simplest to define each type of variable individually:
- An independent variable is a value independent of other variables in scientific research. It is what the researcher changes to trigger an effect on other variables.
- A dependent variable is a value influenced by changes in the independent variable. Therefore, the difference between independent vs. dependent variables is that the former is the cause while the latter is the effect.
You design an experiment to determine whether changes in room lighting can affect test score results:
- Independent variable: Light in the room.
So, you can place participants in a room with different light levels. In contrast, your
- Dependent variable: The test scores.
So, you will assess the participants’ scores using a standard test to determine how their scores differ depending on the room lighting
Independent vs. dependent variables in research
Independent and dependent variables are applied in experimental and quasi-experimental research. Check out the following examples of research questions and their corresponding independent vs. dependent variables:
In experimental research, you analyze the results by visualizing your findings or using descriptive statistics . T-tests and ANOVAs are perfect for analyzing data and answering research questions. There are different types of independent vs. dependent variables in research. The following will delve into the various types of independent vs. dependent variables.
Types of independent variables
There are two key types of independent variables:
- Experimental independent variables
Researchers manipulate independent variables in experiments to evaluate and observe how they impact the dependent variables. For instance, you can apply only two levels to determine if the independent variable impacts the dependent variable.
You design an experiment to determine the impact of a novel medication on diabetic patients’ blood sugar levels. The independent variable will be the medication you vary between the groups.
You can have three independent variable levels applied to different groups:
- Low dose group
Subject variables are the values or qualities that vary across subjects that the researcher cannot manipulate, like age, gender, ethnicity, and race. A researcher cannot randomly assign subject variables to participants. Instead, you must create an experimental design where you can compare the outcomes of subject groups with specific characteristics. Subject variables are applicable in quasi-experimental designs with no random variable assignments. Unfortunately, non-random assignment risks research biases like sampling and selection bias.
You study whether age affects neural responses to digital technology. Your independent variable will be the subjects’ age, which is a subject variable. You can have ages 13 – 23, 24 – 24, and 35 and above.
Your dependent variable will be the neural responses to digital technology. So, you will record the brain activity using MRI scans when the participants hear of digital technology.
After gathering the data from your independent vs. dependent variables, you will check the statistical significance differences between the group.
A distinction between independent vs. dependent variables is that dependent variables are the changes that occur from manipulations of the independent variable. The records that researchers note after manipulating an independent variable are the dependent variable.
Detecting independent vs. dependent variables
Identifying independent vs. dependent variables in an academic or complex research paper can be difficult because independent vs. dependent variables vary from one study to another. Below are guidelines for distinguishing independent vs. dependent variables.
Identifying independent variables
Ask yourself the questions below.
- Is the researcher manipulating or controlling the variable as a subject for grouping the subjects in the study?
- Does the variable precede the other variable (in time)?
- Is the researcher attempting to study if or how the variable affects another variable?
Identifying dependent variables
Ask the following questions.
- Is the variable measured as the research outcome?
- Does the variable rely on another variable in the experiment?
- Does the researcher measure the variable after altering another variable?
Illustrating independent vs. dependent variables
Another important thing to learn is illustrating independent vs. dependent variables. You can use charts or graphs to illustrate independent vs. dependent variables in quantitative research .
The dependent variables usually go on the x-axis, whereas the independent variables are on the y-axis. The independent vs. dependent variables illustration type will depend on your formulated research question.
- Bar charts are perfect for categorical independent variables
- Line or scatter pot graphs are perfect where both your variables are quantitative
You collect data on the blood sugar levels of diabetic patients before and after a novel treatment over a specific period. Place the independent variable, the treatment level, on the x-axis, and the dependent variable, the blood sugar level, on the y-axis.
Plot bars for each treatment group before and after the treatment to illustrate the blood sugar difference. It will show a slight difference in blood sugar levels in the placebo and low-dose subject groups and substantial improvements in the high-dose group.
What are independent and dependent variables?
The difference between independent vs. dependent variables is that independent variables are manipulated in research, while the dependent variables are affected by the changes in other variables.
Can one variable be both independent and dependent?
No, there is a difference in independent vs. dependent variables. So, a value can be dependent or independent, but not both.
Can you use more than one independent or dependent variable in research?
Yes, despite the independent vs. dependent variables distinctions, you can use more than one of each in a complex study with multiple research questions.
What is the key distinction between independent vs. dependent variables?
The key difference between independent vs. dependent variables is that independent variables are the cause, while dependent variables are the effect.
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Dependent Variable The variable that depends on other factors that are measured. These variables are expected to change as a result of an experimental manipulation of the independent variable or variables. It is the presumed effect.
Independent Variable The variable that is stable and unaffected by the other variables you are trying to measure. It refers to the condition of an experiment that is systematically manipulated by the investigator. It is the presumed cause.
Cramer, Duncan and Dennis Howitt. The SAGE Dictionary of Statistics . London: SAGE, 2004; Penslar, Robin Levin and Joan P. Porter. Institutional Review Board Guidebook: Introduction . Washington, DC: United States Department of Health and Human Services, 2010; "What are Dependent and Independent Variables?" Graphic Tutorial.
Identifying Dependent and Independent Variables
Don't feel bad if you are confused about what is the dependent variable and what is the independent variable in social and behavioral sciences research . However, it's important that you learn the difference because framing a study using these variables is a common approach to organizing the elements of a social sciences research study in order to discover relevant and meaningful results. Specifically, it is important for these two reasons:
- You need to understand and be able to evaluate their application in other people's research.
- You need to apply them correctly in your own research.
A variable in research simply refers to a person, place, thing, or phenomenon that you are trying to measure in some way. The best way to understand the difference between a dependent and independent variable is that the meaning of each is implied by what the words tell us about the variable you are using. You can do this with a simple exercise from the website, Graphic Tutorial. Take the sentence, "The [independent variable] causes a change in [dependent variable] and it is not possible that [dependent variable] could cause a change in [independent variable]." Insert the names of variables you are using in the sentence in the way that makes the most sense. This will help you identify each type of variable. If you're still not sure, consult with your professor before you begin to write.
Fan, Shihe. "Independent Variable." In Encyclopedia of Research Design. Neil J. Salkind, editor. (Thousand Oaks, CA: SAGE, 2010), pp. 592-594; "What are Dependent and Independent Variables?" Graphic Tutorial; Salkind, Neil J. "Dependent Variable." In Encyclopedia of Research Design , Neil J. Salkind, editor. (Thousand Oaks, CA: SAGE, 2010), pp. 348-349;
Structure and Writing Style
The process of examining a research problem in the social and behavioral sciences is often framed around methods of analysis that compare, contrast, correlate, average, or integrate relationships between or among variables . Techniques include associations, sampling, random selection, and blind selection. Designation of the dependent and independent variable involves unpacking the research problem in a way that identifies a general cause and effect and classifying these variables as either independent or dependent.
The variables should be outlined in the introduction of your paper and explained in more detail in the methods section . There are no rules about the structure and style for writing about independent or dependent variables but, as with any academic writing, clarity and being succinct is most important.
After you have described the research problem and its significance in relation to prior research, explain why you have chosen to examine the problem using a method of analysis that investigates the relationships between or among independent and dependent variables . State what it is about the research problem that lends itself to this type of analysis. For example, if you are investigating the relationship between corporate environmental sustainability efforts [the independent variable] and dependent variables associated with measuring employee satisfaction at work using a survey instrument, you would first identify each variable and then provide background information about the variables. What is meant by "environmental sustainability"? Are you looking at a particular company [e.g., General Motors] or are you investigating an industry [e.g., the meat packing industry]? Why is employee satisfaction in the workplace important? How does a company make their employees aware of sustainability efforts and why would a company even care that its employees know about these efforts?
Identify each variable for the reader and define each . In the introduction, this information can be presented in a paragraph or two when you describe how you are going to study the research problem. In the methods section, you build on the literature review of prior studies about the research problem to describe in detail background about each variable, breaking each down for measurement and analysis. For example, what activities do you examine that reflect a company's commitment to environmental sustainability? Levels of employee satisfaction can be measured by a survey that asks about things like volunteerism or a desire to stay at the company for a long time.
The structure and writing style of describing the variables and their application to analyzing the research problem should be stated and unpacked in such a way that the reader obtains a clear understanding of the relationships between the variables and why they are important. This is also important so that the study can be replicated in the future using the same variables but applied in a different way.
Fan, Shihe. "Independent Variable." In Encyclopedia of Research Design. Neil J. Salkind, editor. (Thousand Oaks, CA: SAGE, 2010), pp. 592-594; "What are Dependent and Independent Variables?" Graphic Tutorial; “Case Example for Independent and Dependent Variables.” ORI Curriculum Examples. U.S. Department of Health and Human Services, Office of Research Integrity; Salkind, Neil J. "Dependent Variable." In Encyclopedia of Research Design , Neil J. Salkind, editor. (Thousand Oaks, CA: SAGE, 2010), pp. 348-349; “Independent Variables and Dependent Variables.” Karl L. Wuensch, Department of Psychology, East Carolina University [posted email exchange]; “Variables.” Elements of Research. Dr. Camille Nebeker, San Diego State University.
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Independent and Dependent Variables
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In research, a variable is any characteristic, number, or quantity that can be measured or counted in experimental investigations . One is called the dependent variable, and the other is the independent variable.
In research, the independent variable is manipulated to observe its effect, while the dependent variable is the measured outcome. Essentially, the independent variable is the presumed cause, and the dependent variable is the observed effect.
Variables provide the foundation for examining relationships, drawing conclusions, and making predictions in research studies.
In psychology, the independent variable is the variable the experimenter manipulates or changes and is assumed to directly affect the dependent variable.
It’s considered the cause or factor that drives change, allowing psychologists to observe how it influences behavior, emotions, or other dependent variables in an experimental setting. Essentially, it’s the presumed cause in cause-and-effect relationships being studied.
For example, allocating participants to drug or placebo conditions (independent variable) to measure any changes in the intensity of their anxiety (dependent variable).
In a well-designed experimental study , the independent variable is the only important difference between the experimental (e.g., treatment) and control (e.g., placebo) groups.
By changing the independent variable and holding other factors constant, psychologists aim to determine if it causes a change in another variable, called the dependent variable.
For example, in a study investigating the effects of sleep on memory, the amount of sleep (e.g., 4 hours, 8 hours, 12 hours) would be the independent variable, as the researcher might manipulate or categorize it to see its impact on memory recall, which would be the dependent variable.
In psychology, the dependent variable is the variable being tested and measured in an experiment and is “dependent” on the independent variable.
In psychology, a dependent variable represents the outcome or results and can change based on the manipulations of the independent variable. Essentially, it’s the presumed effect in a cause-and-effect relationship being studied.
An example of a dependent variable is depression symptoms, which depend on the independent variable (type of therapy).
In an experiment, the researcher looks for the possible effect on the dependent variable that might be caused by changing the independent variable.
For instance, in a study examining the effects of a new study technique on exam performance, the technique would be the independent variable (as it is being introduced or manipulated), while the exam scores would be the dependent variable (as they represent the outcome of interest that’s being measured).
Examples in Research Studies
For example, we might change the type of information (e.g., organized or random) given to participants to see how this might affect the amount of information remembered.
In this example, the type of information is the independent variable (because it changes), and the amount of information remembered is the dependent variable (because this is being measured).
For the following hypotheses, name the IV and the DV.
1. Lack of sleep significantly affects learning in 10-year-old boys.
2. Social class has a significant effect on IQ scores.
3. Stressful experiences significantly increase the likelihood of headaches.
4. Time of day has a significant effect on alertness.
To ensure cause and effect are established, it is important that we identify exactly how the independent and dependent variables will be measured; this is known as operationalizing the variables.
Operational variables (or operationalizing definitions) refer to how you will define and measure a specific variable as it is used in your study. This enables another psychologist to replicate your research and is essential in establishing reliability (achieving consistency in the results).
For example, if we are concerned with the effect of media violence on aggression, then we need to be very clear about what we mean by the different terms. In this case, we must state what we mean by the terms “media violence” and “aggression” as we will study them.
Therefore, you could state that “media violence” is operationally defined (in your experiment) as ‘exposure to a 15-minute film showing scenes of physical assault’; “aggression” is operationally defined as ‘levels of electrical shocks administered to a second ‘participant’ in another room.
In another example, the hypothesis “Young participants will have significantly better memories than older participants” is not operationalized. How do we define “young,” “old,” or “memory”? “Participants aged between 16 – 30 will recall significantly more nouns from a list of twenty than participants aged between 55 – 70” is operationalized.
The key point here is that we have clarified what we mean by the terms as they were studied and measured in our experiment.
If we didn’t do this, it would be very difficult (if not impossible) to compare the findings of different studies to the same behavior.
Operationalization has the advantage of generally providing a clear and objective definition of even complex variables. It also makes it easier for other researchers to replicate a study and check for reliability .
For the following hypotheses, name the IV and the DV and operationalize both variables.
1. Women are more attracted to men without earrings than men with earrings.
2. People learn more when they study in a quiet versus noisy place.
3. People who exercise regularly sleep better at night.
Can there be more than one independent or dependent variable in a study?
Yes, it is possible to have more than one independent or dependent variable in a study.
In some studies, researchers may want to explore how multiple factors affect the outcome, so they include more than one independent variable.
Similarly, they may measure multiple things to see how they are influenced, resulting in multiple dependent variables. This allows for a more comprehensive understanding of the topic being studied.
What are some ethical considerations related to independent and dependent variables?
Ethical considerations related to independent and dependent variables involve treating participants fairly and protecting their rights.
Researchers must ensure that participants provide informed consent and that their privacy and confidentiality are respected. Additionally, it is important to avoid manipulating independent variables in ways that could cause harm or discomfort to participants.
Researchers should also consider the potential impact of their study on vulnerable populations and ensure that their methods are unbiased and free from discrimination.
Ethical guidelines help ensure that research is conducted responsibly and with respect for the well-being of the participants involved.
Can qualitative data have independent and dependent variables?
Yes, both quantitative and qualitative data can have independent and dependent variables.
In quantitative research, independent variables are usually measured numerically and manipulated to understand their impact on the dependent variable. In qualitative research, independent variables can be qualitative in nature, such as individual experiences, cultural factors, or social contexts, influencing the phenomenon of interest.
The dependent variable, in both cases, is what is being observed or studied to see how it changes in response to the independent variable.
So, regardless of the type of data, researchers analyze the relationship between independent and dependent variables to gain insights into their research questions.
Can the same variable be independent in one study and dependent in another?
Yes, the same variable can be independent in one study and dependent in another.
The classification of a variable as independent or dependent depends on how it is used within a specific study. In one study, a variable might be manipulated or controlled to see its effect on another variable, making it independent.
However, in a different study, that same variable might be the one being measured or observed to understand its relationship with another variable, making it dependent.
The role of a variable as independent or dependent can vary depending on the research question and study design.
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Independent and Dependent Variable Examples Across Different Disciplines
- DESCRIPTION Flowers Independent and Dependent Variable Examples
- SOURCE Flower 1: pinstock / E+ / Getty Images / Flower 2: PM Images / Stone / Getty Images
- PERMISSION Used under Getty Images license
A variable is something that researchers are studying in a research project or experiment. Every scientific experiment involves at least one independent variable and one dependent variable. Discover the difference between these two types of variables and review several examples of each type.
Independent vs. Dependent Variables
Well-designed research projects require different types of variables. But what's the difference between independent and dependent variables? Their definitions can help you see the differences.
- independent variable - the variable that the research changes (for example, the weight-control medication that a certain research group gets)
- dependent variable - the variable that the researcher is testing and measuring in relation to the independent variable (for example, how much weight the research group actually loses)
The researcher determines whether manipulating the independent variable leads to different outcomes regarding the dependent variable. Basically, the dependent variable depends on the independent variable (also known as a treatment variable).
Independent and Dependent Variables Examples
There are many independent and dependent variables examples in scientific experiments, as well as academic and applied research . You even use these variables in your daily life! For example, when you try out a new workout routine or diet (the independent variable), you measure how beneficial it was in your day (the dependent variable). Take a look at these independent and dependent variables examples in multiple disciplines.
Carb Loading and Endurance
An exercise physiologist wonders if carb loading (eating a lot of carbohydrates) the day before participating in endurance activities (such as triathlons or marathons) impacts performance.
- independent variable - quantity of carbohydrates consumed within a defined timeframe
- dependent variable - performance in an endurance activity
A scientist studies the impact of a drug on cancer. She administers the drug to a research group and a placebo to a control group.
- independent variable - administration of the drug (such as dosage or timing)
- dependent variable - the drug's impact on cancer
Rats and Affection
A scientist studies the impact of withholding affection from rats. One group receives a lot of affection, while the other receives none.
- independent variable - amount of affection
- dependent variable - reaction of the rats
A researcher explores whether people who already speak multiple languages learn new languages faster than people who only speak one language.
- independent variable - number of languages spoken
- dependent variable - amount of time to master a new language
Education and Earnings
A researcher wants to know if education level impacts how much a person earns in their job. She studies the amount of education a person has in their life to their current earnings.
- independent variable - highest level of educational attainment
- dependent variable - earnings (salary or wages)
National Origin and Net Worth
A social scientist wonders if there is an association between a person's national origin and their wealth, measured as net worth.
- independent variable - a person's country of origin
- dependent variable - a person's financial net worth
Time Spent Studying and Academic Success
An educational researcher explores whether there is a link between the amount of time someone spends studying and the grade they get in a particular class.
- independent variable - amount of time spent studying for a particular class
- dependent variable - grade in the class
Job Satisfaction and Pay
A human resources professional wonders if how much money a person earns can impact the extent to which an individual experiences job satisfaction.
- independent variable - compensation (salary or wages)
- dependent variable - job satisfaction
Sunlight and Plant Growth
A botanist wonders if the amount of direct sunlight a plant receives impacts how quickly it grows.
- independent variable - amount of direct sunlight plant receives
- dependent variable - speed of plant growth
Airline Travel and Influenza Infection
A medical researcher wonders if the amount of airline travel a person engages in impacts how likely they are to catch influenza during flu season.
- independent variable - amount of airline travel
- dependent variable - influenza infections
Chiropractic Treatments and Migraines
A scientific researcher wonders if regular chiropractic care decreases the frequency and/or severity of migraine headache episodes
- independent variable - how often chiropractic care is received
- dependent variables - frequency of migraine episodes; severity of migraine episodes
Socioeconomic Status and Number of Children
A social scientist explores if there is a link between socioeconomic status and the number of children someone has.
- independent variable - socioeconomic status
- dependent variable - number of children
News Viewership and Knowledge of Facts
A media studies researcher wonders if the amount of time a person spends watching television news contributes to how much factual information people know about current events.
- independent variable - amount of time a person watches TV news
- dependent variable - how much factual information a person knows about current events
Making Sense of Variables
Scientific research questions, experiments and statistical data analysis can get very complex. Learning how to recognize the difference between independent and dependent variables will provide you with a strong foundation before you start learning about other types of variables . To further expand your research skills, review some examples of research paper purpose statements .