This is today’s most complete guide to regression analysis with Microsoft® Excel for any business analytics or research task. Drawing on 25 years of advanced statistical experience, Microsoft MVP Conrad Carlberg shows how to use Excel’s regression-related worksheet functions to perform a wide spectrum of practical analyses.
Carlberg clearly explains all the theory you’ll need to avoid mistakes, understand what your regressions are really doing, and evaluate analyses performed by others. From simple correlations and t-tests through multiple analysis of covariance, Carlberg offers hands-on, step-by-step walkthroughs using meaningful examples.
He discusses the consequences of using each option and argument, points out idiosyncrasies and controversies associated with Excel’s regression functions, and shows how to use them reliably in fields ranging from medical research to financial analysis to operations.
- Understand what regression analysis can and can’t do, and why
- Master regression-based functions built into all recent versions of Excel
- Work with correlation and simple regression
- Make the most of Excel’s improved LINEST() function
- Plan and perform multiple regression
- Distinguish the assumptions that matter from the ones that don’t
- Extend your analysis options by using regression instead of traditional analysis of variance
- Add covariates to your analysis to reduce bias and increase statistical power
Table of Contents
Chapter 1 Measuring Variation: How Values Differ
Chapter 2 Correlation
Chapter 3 Simple Regression
Chapter 4 Using the LINEST( ) Function
Chapter 5 Multiple Regression
Chapter 6 Assumptions and Cautions Regarding Regression Analysis
Chapter 7 Using Regression to Test Differences Between Group Means
Chapter 8 The Analysis of Covariance