![]() In multiple regression, the criterion is predicted by two or more variables. ![]() In simple linear regression, a criterion variable is predicted from one predictor variable. State the assumptions of multiple regression and specify which aspects of the analysis require assumptions.Test the difference between a complete and reduced model for significance.Define R 2 in terms of proportion explained.Explain why the sum of squares explained in a multiple regression model is usually less than the sum of the sums of squares in simple regression.Explain why a regression weight is called a "partial slope".Explain what R is and how it is related to r.Prerequisites Simple Linear Regression, Partitioning Sums of Squares, Standard Error of the Estimate, Inferential Statistics for b and r
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