Abstract
There are many times in educational and psychological research when you want to predict a criterion, Y, but you want to find out if you can develop a better prediction model by using several predictors to predict Y instead of a single predictor as we discussed in Chap. 6 of this book. The resulting statistical procedure is called “multiple correlation” because it uses two or more predictors, each weighed differently in an equation, to predict Y. The job of multiple correlation is to determine if using several predictors can do a better job of predicting Y than any single predictor by itself. The equation for multiple correlation is presented, explained, and a practical business problem is used to present the Excel commands needed to find the multiple correlation and the multiple regression equation generated from the data set. Excel commands are also used to create a SUMMARY OUTPUT which gives the coefficients needed to write the multiple regression equation for the data. Finally, the Excel commands needed to find the correlation between all the variables are explained so that you can create a “correlation matrix” for your data set. You will learn how to read this correlation matrix to determine the correlation between any two variables in your study. Three practice problems are given at the end of the chapter to test your Excel skills, and the answers to these problems appear in Chap. 9 of this book. An additional practice problem is presented in the Practice Test given in Chap. 10 along with its answer in Chap. 11 of this book.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
ESPN. (2009a). NFL Team Total Offense Statistics. http://espn.go.com/nfl/statistics/team/_/stat/total/year/2009. Retrieved 9 Dec 2010.
ESPN. (2009b). NFL Team Total Defense Statistics. http://espn.go.com/nfl/statistics/team/_/stat/total/position/defense/year/2009. Retrieved 9 Dec 2010.
Keller, G. (2009). Statistics for management and economics (8th ed.). Mason, OH: South-Western Cengage Learning.
Levine, D. M., Stephan, D. F., Krehbiel, T. C., & Berenson, M. L. (2011). Statistics for managers using Microsoft Excel (6th ed.). Boston, MA: Prentice Hall/Pearson.
National Football League. (2009). Standings [2009 Regular Season by league]. http://www.nfl.com/standings?category=league&season=2009-REG&split=Overall. Retrieved 9 Dec 2010.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer Science+Business Media New York
About this chapter
Cite this chapter
Quirk, T.J. (2012). Multiple Correlation and Multiple Regression. In: Excel 2007 for Educational and Psychological Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-3725-3_7
Download citation
DOI: https://doi.org/10.1007/978-1-4614-3725-3_7
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4614-3724-6
Online ISBN: 978-1-4614-3725-3
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)