Question 3 Recent research has shown that professors are among the most stressed

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Question 3

Recent research has shown that professors are among the most stressed workers. The output below shows the results of a regression using several variables to predict stress among professors. (Data from Cooper, 1988).

Based on the output above, which of the predictors is significantly related to burnout? Check all that apply.

A

Stress from research

B

Perceived control

C

Stress from teaching

D

Stress from providing pastoral care

Question 4

Using the same output from Question 3, how would we interpret the b-value of perceived control? Please use Model 3 to answer this question.

A

As perceived control increases by .675 units, burnout increases by one unit controlling for the other variables.

B

As perceived control increases by 8.271 units, burnout increases by one unit.

C

As perceived control increases by one unit, burnout increases by .675 units.

D

As perceived control increases by one unit, burnout increases by .675 units, controlling for the other variables.

Question 5 =

Again using the output from Question 3, which variables would we consider eliminating from our model due to concerns of multicollinearity?

A

Stress from research

B

Perceived control

C

Stress from teaching

D

Stress from providing pastoral care

Question 6 pts

Which statistic is useful for assessing the influence of a single predictor in a linear regression? Check all that apply.

A

R2 change.

B

t-statistic.

C

Unstandardized B

D

Chi Square

Question 7 pts

Which of the following are potential sources of bias in a linear model?

A

Z-scores and influential cases

B

Coefficients and outliers

C

T-statistics and influential cases

D

Outliers and influential cases

Question 8 pts

The head of retail sales at a large cosmetic company was interested in determining what the best marketing model was for launching a forthcoming new product to ensure high sales. She ran two separate simple linear regressions; the first used money spent on social media marketing as a predictor and the second had money spent on print media as a predictor. The model featuring social media marketing as a predictor had a R2 of .665, an adjusted R2 of .661, an F-statistic of 112.56 (p < .001). The model featuring print media marketing as a predictor had a R2 of .705, an adjusted R2 of .15, an F-statistic of 34 (p < 0.001). Which marketing model should she invest in, based on these findings, to generate predicted higher sales?

A

The model featuring print media marketing as a predictor is the better of the two models.

B

The model featuring social media marketing as a predictor is the better of the two models.

C

Neither model is effective.

D

The model featuring social media as a predictor is better but biased.

Question 9 pts

A researcher was interested in examining what factors influenced children’s scores in a fitness test. He ran a multiple linear regression, which included four predictors (‘hours spent taking part in physical activity per day’, ‘calories consumed per day’, ‘BMI’, and ‘hours spent watching TV per day’).   His model had a R2 of .739, an adjusted R2 of .742, an F-statistic of 109.46 (p < .001). How would you interpret his findings?

A

It is not a significant model.

B

It is a significant model where the four predictors account for 74% of the variance in the children’s scores in the fitness test.

C

It is a significant model where the four predictors account for 109% of the variance in the children’s scores in the fitness test.

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Question 101 pts

The same researcher noticed that his residual scatterplot seemed to violate homoscedasticity. What should he do in order to ensure that his model is robust?

A

Throw out any outliers and re-run the model.

B

Run the model as a stepwise regression so he can manually throw out any bad predictors.

C

Perform bootstrapping.

D

Without seeing the scatterplot, we can’t tell what he should do.

A

Stress from research

B

Perceived control

Coefficients Standardi zed Coefficien ts Beta Unstandardized Coefficients Collinearity Statistics Tolerance Model Std. Error 1.558 088 054 3.476 084 070 079 3.615 082 067 087 065 Si VIF (Constant) Perceived Control Coping Ability (Constant) Perceived Control Coping Ability Stress from Teachingg (Constant) Perceived Control Coping Ability Stress from Teaching Stress from providing pastoral Care 548 619 372 10.119 633 516 .240 6.166 675 507 360 182 352 7.002 6.851 2.911 7.548 7.383 3.042 1.706 8.271 7.595 4.143 2.775 726 496 1.465 1.465 683 485 683 2 005 507 673 .257 681 370 430 1.469 2.703 2.326 003 093 541 663 .387 193 658 369 322 578 1.520 2.708 3.104 1.730 007 a. Dependent Variable: Burnout

Explanation / Answer

3)
A) stress from research is correct
as p-value for rest of variables < 0.05

4)
when we increase one variable by one unit keeping other variable constant
then there is change in y by coefficient of variable
D) is correct

6)
B) t-statistics

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