1.Adding more regressors to a regression model is always desirable because it may increase the R2.

True

False

2. A prediction interval of a future response of y at an observation x is always wider than a confidence interval for the same observation of x.

True

False

3. Adjusted R2 will not necessarily increase when adding more regressors to a regression model.

True

False

4. A variance inflation factor greater than 10 for a regressor x1 implies that x1 is linearly related to the other regressors.

True

False

5. Normal probability plot of the observed ys is used to check the normality assumption of the errors.

True

False

6. Data transformation can be used when some of the model assumptions are violated.

True

False

7. A large h_ii implies that a point has high leverage.

True

False

8. Calculate a 95% confidence interval for Beta 1 (please refer to previousattachement - Minitab output)

(-0.13236, -0.0199)

(-0.1938, 0.0416)

(-0.24482, 0.09256)

Not available

9.In a regression problem with n = 40 observations, and 4 parameters (including the intercept), what is the distribution of a deleted residual?

Normal distribution

t-distribution with 35 degrees of freedom

t-distribution with 36 degrees of freedom

none of the above

10. If the xs are considered to be fixed numbers, in the 95% statement in the confidence interval what is assumed about the xs in hypothetical future sample?

Observations of y are obtained at the same x values

Observations of y are obtained at random x values

Observations of y are obtained at a subset of the same x values

Does not matter

11. By adding any new regressors to a regression model, the R2 of the new model

will not change

will not decrease

will not increase

depends on which regressors are added