What are the differences between independent variables and dependent variables?

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The differences between independent variables and dependent variables can be summarized as follows:

Definition: An independent variable is a factor that researchers manipulate or control in an experiment to observe its effect on the dependent variable. The dependent variable, on the other hand, is the variable being measured or observed to determine the impact of the independent variable.

Cause and effect: Independent variables are believed to influence or cause changes in the dependent variable. The independent variable is considered the potential cause, while the dependent variable is the outcome or response that may be influenced by the independent variable.

Control and manipulation: Researchers have control over the independent variable as they can manipulate or change its values. They can assign different levels or conditions to the independent variable to observe its impact on the dependent variable. The dependent variable is measured or observed based on the changes in the independent variable.

Research design: The independent variable is typically manipulated or controlled by the researcher in experimental designs to establish cause-and-effect relationships. The dependent variable is measured or observed to assess the effects of the independent variable. In non-experimental designs, the independent variable is naturally occurring and not manipulated.

Relationship: The relationship between the independent and dependent variables is crucial in research. The researcher aims to determine whether changes in the independent variable lead to changes in the dependent variable. The nature and strength of this relationship are explored through statistical analysis and interpretation of research findings.