Correlation measures how two things are related. A positive correlation means they go up together, while a negative correlation means one goes up as the other goes down. A correlation close to zero means there's no clear relationship. Linear regression finds the best line to predict one thing from another. The direction of the line matters, and swapping the variables changes the line. The goodness of fit is measured by R2, which is related to the correlation coefficient. The sign of the regression coefficient shows how the independent variable affects the dependent variable.