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Statistical Analysis of Factors Influencing GPA: Pearson and Spearman Correlations, Regression Models, and Interpretation

An assignment analyzing GPA factors using statistical correlation and regression models.

Michael Davis
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1Statistical Analysis of Factors Influencing GPA: Pearson and SpearmanCorrelations, Regression Models, and InterpretationThe dataset consist of the followingvariablesunder study:1. GPA (Grade Point Average)–Dependentvariable in this study,measured on ratio scale.2. SAT (Scores of Scholastic Aptitude Test)–Independentvariable in this study, measured onratio scale.3. STUDY (No. of hours of study)–Independentvariable in this study, measured on ratio scale.4. WORK (No. of hours of work)–Independentvariable in this study, measured on ratio scale.A fictitious data of49 observations on each of the variables was generated for this analysis.Derived variables:1. exc_gpa : if GPA > 3.51 then exc_gpa =1;else exc_gpa =0. Created to conductlogisticregression.2. RES_GPA_Study: Residualsafter running a linear regression of GPA (dependent variable) onSTUDY(Independent variable). Created for computing semi-partial correlation.All the SPSS outputsare availablein the APPENDIX at the endof this document.(A)Pearson Correlation: Identify two variables for which you could calculate a Pearsoncorrelation coefficient. Describe the variables and their scale of measurement. Now, assume youconducted a Pearson correlation and came up with a significant positive or negative value. Createa mock r value (for example, .3 or-.2). Report your mock finding in APA style (note the text

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Statistics

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