Independent & Dependent Variable Identification
Practice identifying independent variables (IV) and dependent variables (DV) in classic psychology research scenarios, with instant feedback and clear explanations.
What are the IV and DV?
In a psychology experiment, the independent variable (IV) is the factor the researcher deliberately manipulates or changes between groups or conditions. It is the presumed cause.
The dependent variable (DV) is the outcome that is measured to see whether the IV had an effect. It is the presumed effect.
A common trap is to confuse the DV with a confound — an uncontrolled factor such as age or mood that also varies. Only variables that are intentionally manipulated (IV) or measured as the outcome (DV) count.
How to practice
Follow these steps:
- Read the scenario and ask: what did the researcher change or assign? That is likely the independent variable.
- Ask: what did the researcher measure to see the result? That is the dependent variable.
- Select your answers from the two dropdowns.
- Check your answer and read the explanation, then move to the next scenario.
Worked example
A researcher gives one group a new teaching app and another group traditional worksheets, then compares their test scores.
Frequently Asked Questions
Have another question? Let us know.
What is the difference between an independent variable and a dependent variable?
The independent variable (IV) is what the researcher manipulates or assigns — the presumed cause. The dependent variable (DV) is what is measured to see the effect — the presumed outcome. In a study, the IV is changed first and the DV is recorded after.
Can a study have more than one IV or DV?
Yes. Factorial designs manipulate multiple independent variables at the same time (for example, drug dose and gender), and most studies measure more than one dependent variable. For practice purposes here, each scenario focuses on one main IV and one main DV.
Is a confound the same as a dependent variable?
No. A confound is an uncontrolled third variable that varies along with the IV and could explain the results (for example, smarter students choosing a study technique). A DV is the outcome the researcher deliberately measures. Confounds are a threat to validity, not variables to be measured as outcomes.
Why does identifying the IV and DV matter?
Identifying the IV and DV helps you read research critically, understand what a study can actually conclude, and design your own experiments. It also clarifies the causal direction: the IV is manipulated to test its effect on the DV.
