Regression Analysis Microsoft® Excel®

5. Multiple Regression

In This Chapter

A Composite Predictor Variable

Understanding the Trendline

Mapping LINEST()’s Results to the Worksheet

Building a Multiple Regression Analysis from the Ground Up

Using the Standard Error of the Regression Coefficient

Using the Models Comparison Approach to Evaluating Predictors

Estimating Shrinkage in R²

When you move from simple, single-predictor regression to multiple regression, you add one or more predictor variables to the mix. Doing so is very easy to accomplish in the Excel worksheet structure and the function syntax. But it has a major impact on the nature of the analysis, on how you interpret the results, and on the statistical power of the regression.

As to using LINEST() and TREND(), Excel’s ...