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An independent variable is the cause while a dependent variable is the effect in a causal research study.
The independent variable is the factor the researcher controls, while the dependent variable is the one that is measured. The independent and dependent variables are key to any scientific experiment, but how do you tell them apart?
Independent variables and dependent variables are the two fundamental types of variables in statistical modeling and experimental designs. Analysts use these methods to understand the relationships between the variables and estimate effect sizes.
The independent variable is the one you control, while the dependent variable depends on the independent variable and is the one you measure. The independent and dependent variables are the two main types of variables in a science experiment.
The independent variable: the variable that an experimenter changes or controls so that they can observe the effects on the dependent variable. The dependent variable: the variable being measured in an experiment that is “dependent” on the independent variable.
Essentially, the independent variable is the presumed cause, and the dependent variable is the observed effect. In research, the independent variable is manipulated to observe its effect, while the dependent variable is the measured outcome.
Independent variables are the cause—the thing that is changed by the researcher. Dependent variables are the effect—the thing that changes in response to manipulations of the independent variable. In other words, you systematically vary the independent variable and measure the resulting changes in the dependent variable.