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In this set of steps, readers will learn how to conduct a multiple regression procedure. For detailed information regarding the assumptions underlying use of a multiple regression analysis, readers are referred to the Hyperstats Online Statistics Textbook at http://davidmlane.com/hyperstat/ ; to the Electronic Statistics Textbook (2011) at http://www.statsoft.com/textbook/ ; or to Andy Field’s (2009) Discovering Statistics Using SPSS at http://www.amazon.com/Discovering-Statistics-Introducing-Statistical-Method/dp/1847879071/ref=sr_1_1?s=books&ie=UTF8&qid=1304967862&sr=1-1
Research questions for which a multiple regression analysis is appropriate involve determining variables that predict a continuous variable. For example, if you want to predict the life expectancy of individuals and you have archival data available (e.g., health history, gender), then a multiple regression analysis procedure could be utilized. Such a procedure could identify specific variables that are predictive of a long or of a short life expectancy. As such, interventions could be developed and targeted toward the variables that were statistically significant predictors. Other sample research questions for which a multiple regression analysis might be appropriate: (a) What factors predict high scores on a scholastic aptitude measure?; and (b) What factors are predictive of high scores on a life satisfaction scale?
For the purposes of this chapter, our research question is: "What scholastic variables predict students' Full Scale IQ?"
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