4. A researcher conducted a hierarchical regression analysis, entering the predi

Question

4. A researcher conducted a hierarchical regression analysis, entering the predictor conscientiousness into the model first (model 1), followed by morningness (by clicking the next button in SPSS). The criterion (dependent) variable was procrastination. The SPSS output is provided below. For context, the researcher was using the personality variable conscientiousness (higher scores indicate a person that tends to be more responsible and organized) and morningness (higher scores indicate a person that is more morning-oriented; lower scores indicate more evening oriented) to predict academic procrastination. Use = .05 for each relevant test evaluated. (25 points total)

Model Summary

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

Change Statistics

R Square Change

F Change

df1

df2

Sig. F Change

1

.473a

.223

.190

11.20475

.223

6.613

1

23

.017

2

.679b

.460

.411

9.54904

.237

9.667

1

22

.005

a. Predictors: (Constant), conscientiousness

b. Predictors: (Constant), conscientiousness, morningness

Question A.) What is model 1 testing in the ANOVA table? Use the name of the appropriate variable(s) in your description.

Question B.) Is model 1 significant? Report the appropriate F, df, and p-value to support your answer below.

Question C.) What is model 2 testing in the ANOVA table? Use the name(s) of the appropriate variable(s) in your description.

Question D.) Is model 2 significant? Report the appropriate F, df, and p-value to support your answer below.

Question E.) What is the model 2 change testing in the Model Summary Change Statistics table? Hint: This answer should be different from both a and c above.

Question F.) Is model 2 change significant? Report the appropriate F, df, and p-value to support your answer below. What does this indicate in terms of the hierarchical regression analysis? (That is, interpret what is being tested here.)

Please show me how to do this. I'm so confused!

Model Summary

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

Change Statistics

R Square Change

F Change

df1

df2

Sig. F Change

1

.473a

.223

.190

11.20475

.223

6.613

1

23

.017

2

.679b

.460

.411

9.54904

.237

9.667

1

22

.005

a. Predictors: (Constant), conscientiousness

b. Predictors: (Constant), conscientiousness, morningness

Explanation / Answer

a)

procrastination ^ = b0 + b1 *conscientiousness

the model 1 test if b1 = 0

b) p-value = Significance F = 0.017 < 0.05

hence the model 1 is significant

c)   procrastination ^ = b0 + b1 *conscientiousness +b2 * morningness

the model 1 test if b1 = b2 =0

d)

p-value = Significance F = 0.005 < 0.05

hence the model 2 is significant

e)

the model 2 change testing if b2 =0

e)

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