Regression analysis is an extremely valuable quantitative tool. Using scatter diagrams helps to see relationships between variables. The F test is used to determine if the results can be considered useful. The coefficient of determination $\left(r^2\right)$ is used to measure the proportion of variability in Y that is explained by the regression model. The correlation coefficient measures the relationship between two variables.

Multiple regression involves the use of more than one independent variable. Dummy variables (binary or indicator variables) are used with qualitative or categorical data. Nonlinear models can be transformed into linear models.

We saw how to use Excel to develop regression models. Interpretation of computer output was presented, and several examples were provided.