Question 1

Individual predictors cannot be individually associated with the criterion variable if R is not different from 0 (i.e., if the entire model is not significant).

Accepted Answer

Even if the overall model is not significant (R is not different from 0), individual predictors can still have significant associations with the criterion variable. This can occur because the overall model's significance tests the combined effect of all predictors, while individual predictors can have significant effects that are not captured by the overall model test.

Question 2

Multiple regression examines the degree of association between any predictor and the criterion variable controlling for other predictors in the equation.

Accepted Answer

Multiple regression takes into account the influence of multiple predictors on the criterion variable, while controlling for the effects of all other predictors in the equation.

Question 3

In a regression predicting adolescent delinquent behavior from gender, the number of delinquent peers in the social network, and parental under control, R² = .60. This means each of the variables accounted for 36% of the variability in delinquent behavior.

Accepted Answer

The statement is incorrect. R² = .60 indicates that the overall model, including all three variables, accounted for 60% of the variability in delinquent behavior, not 36% as stated. The individual contribution of each variable to the model cannot be determined from this information alone.

Question 4

Any association that was significant as a simple correlation will be significant in a multiple regression equation predicting the same criterion variable.

Accepted Answer

In multiple regression, the significance of an association between a predictor and the criterion variable can change due to the inclusion of other variables. This is because multiple regression accounts for the shared variance among predictors, which can alter the significance and strength of individual associations that appeared significant in simple correlations.

Question 5

If you wanted to identify mothers who needed a parenting intervention to enhance sensitivity and could only collect two pieces of information from each family due to time and costs, which of the measures in the previous example would you select? Why?

Accepted Answer

The answer of If you wanted to identify mothers who...

Question 6

Are the set of predictors significantly associated with maternal sensitivity?

Accepted Answer

The answer of Are the set of predictors significantly associated...

Question 7

Given the information in the following table, create the corresponding regression equation.

Accepted Answer

The answer of Given the information in the following table,...

Question 8

In multiple regression, the criterion variable is predicted by more than one independent variable.

Accepted Answer

In multiple regression, there are two or more independent variables predicting the criterion variable.

Question 9

Based on the previous regression equation you just created, estimate cancer anxiety given the following values. 
a. social support = 100; general anxiety = 50 
b. social support = 25; general anxiety = 7

Accepted Answer

The answer of Based on the previous regression equation you...

Question 10

Stepwise regression procedures capitalize on chance.

Accepted Answer

Stepwise regression procedures involve sequentially adding or removing predictor variables from a model based on their observed impact on the outcome variable. However, this process can be influenced by chance and may result in a final model that happens to fit the data well by luck, rather than because it accurately captures the true relationship between the predictors and outcome variable. Therefore, stepwise regression procedures can capitalize on chance in some cases.

Question 11

Which individual predictors are significantly associated with maternal sensitivity?

Accepted Answer

The answer of Which individual predictors are significantly associated with...

Question 12

Multiple regression allows you to examine the degree of association between individual independent variables and the criterion variable AND the degree of association between the set of independent variables and the criterion variable.

Accepted Answer

Multiple regression takes into account the relationship between each independent variable and the criterion variable as well as the combined relationship of all independent variables with the criterion variable.

Question 13

Based on the same formula ( Ŷ = .75 X -.40 Z + 5), calculate the missing predictor variables based on the following information. 
a. Ŷ = 100; X = 0 
b. Ŷ = 0; Z = -20

Accepted Answer

The answer of Based on the same formula ( Ŷ...

Question 14

R² can range from -1 to 1.

Accepted Answer

R² appears to be a code or identifier rather than a numerical value that can range from -1 to 1.

Question 15

Write a sentence explaining the analysis presented in the following table (i.e., what are the predictor variables, what is the criterion variable).

Accepted Answer

The answer of Write a sentence explaining the analysis presented...

Question 16

Estimate Y based on the equation Ŷ = .75 X -.40 Z + 5 using the following values. 
a. X = 10; Z = 0 
b. X = 0; Z = 0 
c. X = 20; Z = 100

Accepted Answer

The answer of Estimate Y based on the equation Ŷ...

Question 17

How much variability in maternal sensitivity is accounted for by the set of predictors?

Accepted Answer

The answer of How much variability in maternal sensitivity is...

Question 18

How do the regression results vary from the simple correlations presented below? 
Explain why this may be the case.

Accepted Answer

The answer of How do the regression results vary from...

Quiz 11: Multiple Regression