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In this set of steps, readers will learn how to conduct a canonical discriminant analysis procedure. For detailed information regarding the assumptions underlying use of a discriminant analysis, readers are referred to the Hyperstats Online Statistics Textbook at (External Link) ; to the Electronic Statistics Textbook (2011) at (External Link) ; or to Andy Field’s (2009) Discovering Statistics Using SPSS at (External Link)&ie=UTF8&qid=1304967862&sr=1-1
Research questions for which a discriminant analysis procedure is appropriate involve determining variables that predict group membership. For example, if two groups of persons are present such as completers and non-completers and archival data are available, then a discriminant analysis procedure could be utilized. Such a procedure could identify specific variables that differentiate group membership. As such, interventions could be developed and targeted toward the variables that predicted group membership. Other sample research questions for which a discriminant analysis might be appropriate: (a) What factors differentiates successful from unsuccessful students?; (b) What factors differentiate delinquents from nondelinquents?; (c) What set of test scores best differentiates students with LD, students who are failing, and students with MR?; and (d) What set of factors differentiates drop-outs from persisters?
For purposes of this chapter, our research question is: “What scholastic variables differentiate boys from girls?”
First, open up the dataset you intend to analyze for your canonical discriminant analysis.
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