Cause and effect refers to the relationship between two variables where changes in one variable directly influence changes in another variable. It implies that one variable causes or leads to changes in another variable.
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Correlation: Correlation describes the relationship between two variables without implying causation. It measures how closely related two variables are.
Confounding Variable: A confounding variable is an extraneous factor that influences both the independent and dependent variables, making it difficult to determine cause and effect.
Experimental Design: Experimental design involves planning and conducting experiments to investigate cause-and-effect relationships by manipulating independent variables and measuring their effects on dependent variables.