SAS Essentials: Mastering SAS for Data Analytics, 2nd Edition

12CORRELATION AND REGRESSION

LEARNING OBJECTIVES

• To be able to use SAS^® procedures to calculate Pearson and Spearman correlations
• To be able to use SAS procedures to produce a matrix of scatterplots
• To be able to use SAS procedures to perform simple linear regression
• To be able to use SAS procedures to perform multiple linear regression
• To be able to use SAS procedures to calculate predictions using a model
• To be able to use SAS procedures to perform residual analysis

Correlation measures the association between two quantitative variables, and the closely related regression analysis uses the relationship between independent and dependent variables for predicting the dependent (response or outcome) variable using one or more independent (predictor or explanatory) variables. In simple linear regression, there is a single dependent variable and a single independent variable, while in multiple linear regression (MLR) there are two or more independent variables. In this chapter, we discuss the use of SAS to perform correlation and regression analyses.

12.1 CORRELATION ANALYSIS USING PROC CORR

Before proceeding to the use of SAS to perform correlation analysis, we first provide a brief discussion of the basics of correlation analysis.

12.1.1 Correlation Analysis Basics

The correlation coefficient is a measure of the linear relationship between two quantitative variables measured on the same subject (or entity). For example, you might want to study the relationship between ...