The coefficient of determination, denoted as $R^2$, measures the proportion of the variance in the dependent variable that is predictable from the independent variable(s) in a regression model. It provides an indication of the goodness-of-fit for the model.
Regression Equation: An equation that describes the relationship between one dependent variable and one or more independent variables.
Correlation Coefficient: A measure that determines the degree to which two variables' movements are associated.
Adjusted R-Squared: A modified version of $R^2$ that adjusts for the number of predictors in a model, providing a more accurate measure when multiple predictors are used.