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1. In each of the following situations, explain what is wrong and why.
(a) One of the assumptions for multiple regression is that the distribution of each explanatory variable is Normal.
(b) The smaller the P-value for the ANOVA F test, the greater the explanatory power of the model.
All explanatory variables that are signi?cantly correlated with the response variable will have a statistically signi?cant regression coef?cient in the multiple regression model. 2. Constructing the ANOVA table. Seven explanatory variables are used to predict a response variable using a multiple regression. There are 140 observations.
(a) Write the statistical model that is the foundation for this analysis. Also include a description of all assumptions.
(b) Outline the analysis of variance table giving the sources of variation and numerical values for the degrees of freedom.
Compute the variance and standard deviation
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