Questions A multiple regression model can incorporate polynomial terms derived f

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A multiple regression model can incorporate polynomial terms derived from regressor variables with each term treated as a new regressor.

a)True

b)False

QUESTION 2

In regression, to model a qualitative (categorical) variable an allocated code such as 1, 2, and 3 is appropriate.

a)True

b)False

QUESTION 3

Forward selection, backward elimination and stepwise regression all lead to the same choice of final model.

a)True

b)False

QUESTION 4

Ridge regression is a regression method that is most useful in situations where there is multicollinearity among regressors.

a)True

b)False

QUESTION 5

An intrinsically linear model can be transformed to an equivalent linear form.

a)True

b)False

QUESTION 6

Adjusted R squared does not necessarily increase as additional regressors are introduced into the model.

a)True

b)False

QUESTION 7

The ridge regression estimator is a linear transformation of the least-squares estimator.

a)True

b)False

QUESTION 8

The breakdown point of ordinary least-squares estimators for a sample of size n is 1/n.

a)True

b)False

QUESTION 9

One way of choosing the proper value for k in ridge regression is to use the ridge trace.

a)True

b)False

Explanation / Answer

1 ) A multiple regression model can incorporate polynomial terms derived from regressor variables with each term treated as a new regressor.

a) True

2 ) In regression, to model a qualitative (categorical) variable an allocated code such as 1, 2, and 3 is appropriate.

a) True

Reason : We assign indicator levels to account for the effect that the variable may have on the response.  

3 ) Forward selection, backward elimination and stepwise regression all lead to the same choice of final model.

b ) False

4 ) Ridge regression is a regression method that is most useful in situations where there is multicollinearity among regressors.

a) True

5 ) An intrinsically linear model can be transformed to an equivalent linear form.

a) True

6 ) Adjusted R squared does not necessarily increase as additional regressors are introduced into the model.

a) True

7 ) The ridge regression estimator is a linear transformation of the least-squares estimator.

a) True

8 ) The breakdown point of ordinary least-squares estimators for a sample of size n is 1/n.

a) True

9 ) One way of choosing the proper value for k in ridge regression is to use the ridge trace.

a) True

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