Question 1

The difference between multiple regression and simple regression is that

Accepted Answer

A)  multiple regression can have more than one dependent variable. 
B)  multiple regression can have more than one independent variable. 
C)  multiple regression does not produce a correlation coefficient. 
D)  both b and c 
A)  multiple regression can have more than one dependent variable. 
B)  multiple regression can have more than one independent variable. 
C)  multiple regression does not produce a correlation coefficient. 
D)  both b and c

Question 2

If two variables taken together account for 65% of the variability in Y , and a third variable has a simple squared correlation with Y of .10, then adding that variable to the equation will allow us to account for

Accepted Answer

A)  65% of the variability in Y . 
B)  75% of the variability in Y . 
C)  10% of the variability in Y . 
D)  at least 65% of the variability in Y . 
A)  65% of the variability in Y . 
B)  75% of the variability in Y . 
C)  10% of the variability in Y . 
D)  at least 65% of the variability in Y .

Question 3

If we predict anxiety from stress and intrusive thoughts, and if the multiple regression is significant, that means that

Accepted Answer

A)  the regression coefficient for stress will be significant. 
B)  the regression coefficient for intrusive thoughts will be significant. 
C)  both variables will be significant predictors. 
D)  We can't tell. 
A)  the regression coefficient for stress will be significant. 
B)  the regression coefficient for intrusive thoughts will be significant. 
C)  both variables will be significant predictors. 
D)  We can't tell.

Question 4

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

a. Z = -23

Question 5

R2 can range from -1 to 1.

Accepted Answer

A) True 
 B)False

Question 6

The statistical tests on regression coefficients are usually

Accepted Answer

A)  t tests. 
B)  z tests. 
C)  F tests. 
D)  r tests. 
A)  t tests. 
B)  z tests. 
C)  F tests. 
D)  r tests.

Question 7

If we know that a regression coefficient is statistically significant, we know that

Accepted Answer

A)  it is positive. 
B)  it is not 0.0. 
C)  it is not 1.0. 
D)  it is large. 
A)  it is positive. 
B)  it is not 0.0. 
C)  it is not 1.0. 
D)  it is large.

Question 8

If you have a number of scores that are outliers you should

Accepted Answer

A)  throw them out. 
B)  run the analysis with and without them, to see what difference they make. 
C)  try to identify what is causing those scores to be outliers. 
D)  both b and c 
A)  throw them out. 
B)  run the analysis with and without them, to see what difference they make. 
C)  try to identify what is causing those scores to be outliers. 
D)  both b and c

Question 9

In simple correlation a squared correlation coefficient tells us the percentage of variability in Y associated with variability in X . In multiple regression, the squared multiple correlation coefficient

Accepted Answer

A)  has the same kind of meaning. 
B)  has no meaning. 
C)  overestimates the degree of variance accounted for. 
D)  underestimates the degree of variance accounted for. 
A)  has the same kind of meaning. 
B)  has no meaning. 
C)  overestimates the degree of variance accounted for. 
D)  underestimates the degree of variance accounted for.

Question 10

A table in which each variable is correlated with every other variable is called

Accepted Answer

A)  a multivariate table 
B)  an intercorrelation matrix 
C)  a contingency table 
D)  a pattern matrix 
A)  a multivariate table 
B)  an intercorrelation matrix 
C)  a contingency table 
D)  a pattern matrix

Question 11

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

Self-esteem and easy temperame

Question 12

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

a. 12.5 
b

Question 13

Which individual predictors are significantly associated with maternal sensitivity?

Accepted Answer

Self-estee

Question 14

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

A) True 
 B)False

Question 15

When we speak of the correlations among the independent variables, we are speaking of

Accepted Answer

A)  homoscedasticity. 
B)  multicollinearity. 
C)  independence. 
D)  multiple correlation. 
A)  homoscedasticity. 
B)  multicollinearity. 
C)  independence. 
D)  multiple correlation.

Question 16

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 17

If the multiple correlation is high, we would expect to have _______ residuals than if the multiple correlation is low.

Accepted Answer

A)  smaller 
B)  larger 
C)  the same as 
D)  We can't tell. 
A)  smaller 
B)  larger 
C)  the same as 
D)  We can't tell.

Question 18

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...

The difference between multiple regression and simple regression is that

If two variables taken together account for 65% of the variability in Y , and a third variable has a simple squared correlation with Y of .10, then adding that variable to the equation will allow us to account for

If we predict anxiety from stress and intrusive thoughts, and if the multiple regression is significant, that means that

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

R² can range from -1 to 1.

The statistical tests on regression coefficients are usually

If we know that a regression coefficient is statistically significant, we know that

If you have a number of scores that are outliers you should

In simple correlation a squared correlation coefficient tells us the percentage of variability in Y associated with variability in X . In multiple regression, the squared multiple correlation coefficient

A table in which each variable is correlated with every other variable is called

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?

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

Which individual predictors are significantly associated with maternal sensitivity?

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.

When we speak of the correlations among the independent variables, we are speaking of

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

If the multiple correlation is high, we would expect to have _______ residuals than if the multiple correlation is low.

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

Introduction

Basic Concepts

Displaying Data

Measures of Central Tendency

Measures of Variability

The Normal Distribution

Basic Concepts of Probability

Sampling Distributions and Hypothesis Testing

Correlation

Regression

Hypothesis Tests Applied to Means: One Sample

Hypothesis Tests Applied to Means: Two Related Samples

Hypothesis Tests Applied to Means: Two Independent Samples

Power

One-Way Analysis of Variance

Factorial Analysis of Variance

Repeated-Measures Analysis of Variance

Chi-Square

Nonparametric and Resampling Statistical Tests

Meta-Analysis

Filters

Exam 11: Multiple Regression

The difference between multiple regression and simple regression is that

If two variables taken together account for 65% of the variability in Y , and a third variable has a simple squared correlation with Y of .10, then adding that variable to the equation will allow us to account for

If we predict anxiety from stress and intrusive thoughts, and if the multiple regression is significant, that means that

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

R2 can range from -1 to 1.

The statistical tests on regression coefficients are usually

If we know that a regression coefficient is statistically significant, we know that

If you have a number of scores that are outliers you should

In simple correlation a squared correlation coefficient tells us the percentage of variability in Y associated with variability in X . In multiple regression, the squared multiple correlation coefficient

A table in which each variable is correlated with every other variable is called

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?

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

Which individual predictors are significantly associated with maternal sensitivity?

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.

When we speak of the correlations among the independent variables, we are speaking of

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

If the multiple correlation is high, we would expect to have _______ residuals than if the multiple correlation is low.

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

Introduction

Basic Concepts

Displaying Data

Measures of Central Tendency

Measures of Variability

The Normal Distribution

Basic Concepts of Probability

Sampling Distributions and Hypothesis Testing

Correlation

Regression

Hypothesis Tests Applied to Means: One Sample

Hypothesis Tests Applied to Means: Two Related Samples

Hypothesis Tests Applied to Means: Two Independent Samples

Power

One-Way Analysis of Variance

Factorial Analysis of Variance

Repeated-Measures Analysis of Variance

Chi-Square

Nonparametric and Resampling Statistical Tests

Meta-Analysis

Filters

R² can range from -1 to 1.

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.