
Categorical variables, such as religion, major field of study or region of residence, need to be recoded to binary (dummy) variables or other types of contrast variables. Data: Dependent and independent variables should be quantitative.


For each model: Consider regression coefficients, correlation matrix, part and partial correlations, multiple R, R2, adjusted R2, change in R2, standard error of the estimate, analysis-of-variance table, predicted values and residuals.For each variable: Consider the number of valid cases, mean and standard deviation.Assumptions to be considered for success with linear-regression analysis:
