In research, variables are any characteristics that can take on different values, such as height, age, temperature, or test scores. Show
Researchers often manipulate or measure independent and dependent variables in studies to test causeandeffect relationships.
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. Your dependent variable is math test scores. You measure the math skills of all participants using a standardized test and check whether they differ based on room temperature. What is an independent variable?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:
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. Types of independent variablesThere are two main types of independent variables.
Experimental variablesIn 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. Example: Independent variable levelsYou are studying the impact of a new medication on the blood pressure of patients with hypertension. Your independent variable is the treatment that you directly vary between groups.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 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 variablesSubject 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 quasiexperimental design because there’s no random assignment. Note that any research methods that use nonrandom assignment are at risk for research biases like selection bias and sampling bias. Example: Quasiexperimental designYou study whether gender identity affects neural responses to infant cries.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. After collecting data, you check for statistically significant differences between the groups. You find some and conclude that gender identity influences brain responses to infant cries. What is a dependent variable?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:
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. Identifying independent vs. dependent variablesDistinguishing 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 variablesUse this list of questions to check whether you’re dealing with an independent variable:
Recognizing dependent variablesCheck whether you’re dealing with a dependent variable:
Independent and dependent variables in researchIndependent and dependent variables are generally used in experimental and quasiexperimental 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: You’ll often use t tests or ANOVAs to analyze your data and answer your research questions. Visualizing independent and dependent variablesIn quantitative research, it’s good practice to use charts or graphs to visualize the results of studies. Generally, the independent variable goes on the xaxis (horizontal) and the dependent variable on the yaxis (vertical). The type of visualization you use depends on the variable types in your research questions:
To inspect your data, you place your independent variable of treatment level on the xaxis and the dependent variable of blood pressure on the yaxis. You plot bars for each treatment group before and after the treatment to show the difference in blood pressure. Based on your results, you note that the placebo and lowdose groups show little difference in blood pressure, while the highdose group sees substantial improvements. Frequently asked questions about independent and dependent variablesWhat’s the definition of an independent variable?
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. Independent variables are also called:
What’s the definition of a dependent variable?
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:
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