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5.) Explain the terms multiple R and R-square. 6.) Describe how beta weights and squared semipartial correlations help determine the unique contribution of each predictor
5.) Explain the terms "multiple R" and "R-square." 6.) Describe how beta weights and squared semipartial correlations help determine the unique contribution of each predictor variable in multiple regression analysis. 7.) Discuss the applications of loglinear analysis and provide one examples in which you would consider using loglinear analysis. 8.) Describe structural equation modeling (SEM) and explain the two variables associated with SEM
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