Reference no: EM132853112
-Explain the linear multiple regression model, the independent variables and the dependent variable, assumptions of the model, as well as the objectives
-Given the data, what approach is taken to construct the model?
-Explain the effect of multicollinearity in multiple regression, and how multicollinearity is detected?
-Show that the estimates of the coefficients are unbiased estimates of actual values.
-Explain the hypotheses on coefficients of the regression and how the results of testing these hypotheses are interpreted about significance of these coefficients? Include both unidirectional and bidirectional situations
-How do you interpret the effect of significant coefficients?
-How the distribution of the observed residuals of the constructed model are tested for normality?
-What is the coefficient of determination, and what is its significance?
-Why the adjusted coefficient of determination is used as an alternative assessment
-How can the regression model be used for prediction?
Explain the computations involved in finding number of ways
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Explain the linear multiple regression model
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