Which procedure is used to perform linear regression analysis?

The procedure used to perform linear regression analysis is PROC REG. This procedure is specifically designed for fitting linear models to data. It lets users analyze the relationships between a dependent variable and one or more independent variables through the model’s coefficients, residuals, and fit statistics.

PROC REG provides output that includes parameter estimates, significance tests, and various diagnostics for checking the validity of the linear regression assumptions. This makes it an essential tool when you need to understand how changes in the predictor variables affect the response variable. Therefore, it is the correct answer for performing linear regression analysis.

In contrast, PROC ANOVA is focused on analysis of variance, which is typically used to compare means across multiple groups rather than modeling relationships. PROC MEANS summarizes data by providing descriptive statistics like mean, median, and standard deviation, without directly fitting a model. PROC FREQ is utilized for frequency analysis for categorical data, focusing on counting occurrences rather than performing regression analysis. These differences clarify why PROC REG is the appropriate choice for performing linear regression.