Final answer:
A moderator variable determines the magnitude of a cause-effect relationship between variables, with regression analysis being a common method to analyze such relationships. The dependent variable is the outcome, while the independent variable is manipulated to determine causation. Correlation does not necessarily imply causation.
Step-by-step explanation:
A moderator variable determines the magnitude of an existing cause-effect relationship between two variables. Thus, a moderator increases or reduces the effect of another cause. Regression analysis is a key statistical method used to uncover the nature of relationships between a dependent variable (the outcome variable) and one or more independent variables (the causal variables).
The dependent variable is the one that is being affected by the manipulation, while the independent variable is the one that is manipulated. To determine the most likely cause and effect relationship, researchers use correlation coefficients to measure how strongly two variables are related, but to establish causality one would typically conduct an experiment with a control group and manipulate the variables to observe the direct effects.
It is essential to note that correlation does not imply causation; a third factor, known as a confounding variable, may actually be influencing the dependent and independent variables, thereby affecting the observed relationship.