Question
State whether the following statements are true or false and also give the reason in support of your answer.
(i) The model Y = BX + & is a linear model.
(ii) If total and residual sum of squares for a dataset are 124 and 15.5, respectively, then the coefficient of determination is 0.875.
(iii) We use Cook's distances to identify the autocorrelation of the error terms.
(iv) If the coefficient of determination for the auxiliary regression model of the explanatory variable X₁ is 0.8, the VIF for X₁ will be 5.
(v) We use baseline category logit models when we have ordered categories of a response variable.
Answer :
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(i) True. The model (Y = \beta X + \epsilon) is considered a linear model because it is linear in parameters (\beta), even if (X) is transformed. Linearity in regression refers to parameters, not necessarily the predictor variables. (ii) True. The coefficient of determination (R^2) is calculated
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