Abstract
Up until now in this book, you have been dealing with the situation in which you have had only one group or two groups of people (or objects) in your research study and only one measurement (i.e., variable) “number” on each of these people. This chapter asks you to change gears again and to deal with the situation in which you are measuring two variables instead of only one variable and you are trying to discover the “relationship” between these variables. For example, if one variable increases in value, does the other variable increase in value (i.e., a “positive” relationship) or decrease in value (i.e., a negative relationship), and is this relationship “weak” or “strong?” The formula for the correlation r is presented, explained, and the nine steps for computing a correlation are explained using a calculator example. Then, the Excel commands for computing a correlation are presented along with the Excel steps needed to create a chart summarizing the relationship between the two variables. You will learn how to use Excel to draw the “best-fit line” through the data points on a scatterplot and how to determine the equation for this line so that you can use this equation to predict one variable from the other variable. You will learn both how to print a chart by itself, and how to print both the table and the chart so that they fit onto a single page, how to print only the chart by itself on a separate page, and how to print only the SUMMARY OUTPUT of the regression analysis so that it fits onto a separate page by itself. Three practice problems are given at the end of the chapter to test your Excel skills, and the answers to these problems appear in Appendix A of this book. An additional practice problem is presented in the Practice Test given in Appendix B along with its answer in Appendix C of this book.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Black, K. Business Statistics: For Contemporary Decision Making (6th ed.). Hoboken, NJ: John Wiley & Sons, Inc., 2010.
Center for American Women and Politics. Retrieved September 2, 2011 from http://www.cawp.rutgers.edu/Facts/Officeholders/stleg.pdf, 2007.
Johnson, J.B. and Reynolds, H.T. Political Science Research Methods (5th ed.). Washington D.C.: CQ Press, 2005.
King, G., Keohane, R.O., and Verba, S. Designing Social Inquiry: Scientific Inference in Qualitative Research. Princeton, NJ: Princeton University Press, 1994.
Levine, D.M.. Stephan, D.F., Krehbiel, T.C., and Berenson, M.L. Statistics for Managers Using Microsoft Excel (6th ed.). Boston, MA: Prentice Hall/Pearson, 2011.
Shively, W.P. The Craft of Political Research (7th ed.). Upper Saddle River, NJ: Prentice Hall/Pearson, 2009.
Steinberg, W.J. Statistics Alive! Thousand Oaks, CA: Sage Publications, 2008.
Zikmund, W.G. and Babin, B.J. Exploring Marketing Research (10th ed.). Mason, OH: South-Western Cengage Learning, 2010.
U.S. Census Bureau. Retrieved September 3, 2011 from http://www.census.gov/compendia/smadb/TableA-22.pdf., 2003.
U.S. Census Bureau. Retrieved September 2, 2011 fromhttp://www.census.gov/compendia/smadb/TableA-01.pdf, 2005.
U.S. Census Bureau. Retrieved September 4, 2011 from http://www.census.gov/compendia/statab/cats/transportaion/motor_vehicle_accidents_and_fatalities.html, Table 1103, 2008.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Quirk, T.J. (2015). Correlation and Simple Linear Regression. In: Excel 2013 for Social Sciences Statistics. Excel for Statistics. Springer, Cham. https://doi.org/10.1007/978-3-319-19177-5_6
Download citation
DOI: https://doi.org/10.1007/978-3-319-19177-5_6
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-19176-8
Online ISBN: 978-3-319-19177-5
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)