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 y’s 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 hii implies that a point has high leverage. True False 8. Calculate a 95% confidence interval for Beta 1 (please refer to previous attachement – 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 x’s are considered to be fixed numbers, in the 95% statement in the confidence interval what is assumed about the x’s 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