Question 1

What types of dependent variables are ok to use for linear regression?

Accepted Answer

A)  interval/ratio variables 
B)  interval/ratio variables and dichotomies 
C)  interval/ratio variables, ordinal variables, and dichotomies 
D)  interval/ratio variables, ordinal variables, and nominal variables 
A)  interval/ratio variables 
B)  interval/ratio variables and dichotomies 
C)  interval/ratio variables, ordinal variables, and dichotomies 
D)  interval/ratio variables, ordinal variables, and nominal variables

Question 2

An analyst is interested in the relationship between number of cats a person has (an independent variable), number of dogs a person has (an independent variable) and the number of friends the person has (the dependent variable). She regresses number of FRIENDS on number of CATS and number of DOGS. The equation for the best-fitting straight line is
FRIENDS = 10 − 2(CATS) + 1(DOGS)
A) A person had 4 cats and 2 dogs. What is that person's predicted number of friends?
B) What is the regression residual for a person with 0 cats, 0 dogs, and 0 friends?

Accepted Answer

The answer of An analyst is interested in the relationship...

Question 3

What proportion of the differences in the dependent variable is explained by the independent variables in the regression equation?

Accepted Answer

A)  .151 
B)  .388 
C)  .612 
D)  .849 
A)  .151 
B)  .388 
C)  .612 
D)  .849

Question 4

If you want to see which factor (age at marriage, educational level, or income) had the strongest net effect on marital happiness, what is an appropriate statistical technique to use?

Accepted Answer

A)  Bivariate Correlation 
B)  Compute 
C)  Explore 
D)  Linear Regression 
A)  Bivariate Correlation 
B)  Compute 
C)  Explore 
D)  Linear Regression

Question 5

In the context of regression analysis, each of the following has at least one other name. State at least one of those other names:

Accepted Answer

a. unstandardized coefficient

Question 6

If you want to see what the cases in your data set are like on a single continuous, interval/ratio variable, what is an appropriate statistical technique to use?

Accepted Answer

A)  Bivariate Correlation 
B)  Compute 
C)  Explore 
D)  Linear Regression 
A)  Bivariate Correlation 
B)  Compute 
C)  Explore 
D)  Linear Regression

Question 7

The regression equation is Y = 50 - 5X1 + 10X2 - 20X3. A case has a value of 1 on X1, 2 on X2, and 3 on X3. What's the predicted value?

Accepted Answer

A)  −2 
B)  5 
C)  35 
D)  48 
A)  −2 
B)  5 
C)  35 
D)  48

Question 8

Answer the questions that follow this SPSS output: 
 
If the three variables in the correlation matrix were all used as independent variables in a single multiple regression analysis, would there be a multicollinearity problem? 
A) State yes or no. __________
B) Justify your answer by referring to one or more statistics in the matrix.

Accepted Answer

a. no
b. None of the

Question 9

According to the following regression equation: INCOME = 9000 + 2500(EDUC) − 100(AGE) − 5000(FEMALE), an increase of one year in education results in how much of a change in income? (State both the amount of change and the direction.)

Accepted Answer

an increas

Question 10

When would you use Crosstabs to look at the net effects of two independent variables on a dependent variable and when would you use Linear Regression?

Accepted Answer

Linear Regression could only be used if

Question 11

If you want to see the net effect of gender on academic achievement after controlling for age and parents' social class, what is an appropriate statistical technique to use?

Accepted Answer

A)  Bivariate Correlation 
B)  Compute 
C)  Frequencies 
D)  Linear Regression 
A)  Bivariate Correlation 
B)  Compute 
C)  Frequencies 
D)  Linear Regression

Question 12

What is multicollinearity and why is it a problem?

Accepted Answer

Multicollinearity is when two or more of

Question 13

Let's say the correlation between SAT scores and college GPA is .70 but when you regress college GPA on SAT scores and parents' social class, the standardized coefficient for SAT scores is .02. What would this tell you?

Accepted Answer

It would indicate that the effect of SAT

Question 14

If you want to see how well percent of classes attended and percent of assigned reading completed do together in accounting for differences in student exam grades, what is an appropriate statistical technique to use?

Accepted Answer

A)  Bivariate Correlation 
B)  Compute 
C)  Explore 
D)  Linear Regression 
A)  Bivariate Correlation 
B)  Compute 
C)  Explore 
D)  Linear Regression

Question 15

What kinds of questions can you answer using multiple regression?

Accepted Answer

Changing a case's values on the independ

Question 16

The regression equation is POVERTY = 10 + 1(UNEMPLOYMENT) - 0.5(COLLEGE). A county has a POVERTY rate of 30, an UNEMPLOYMENT rate of 10, and COLLEGE graduate rate of 10. What is the county's regression residual?

Accepted Answer

A)  −50 
B)  −15 
C)  15 
D)  50 
A)  −50 
B)  −15 
C)  15 
D)  50

Question 17

What is a net effect?

Accepted Answer

A net effect is the influence

Question 18

Answer the questions that follow this SPSS output: 
 
The dependent variable is fallGPA (student's GPA after the fall semester). The independent variables are sizeHS (the size of their high school graduating class) and SAT (their best SAT score). 
A) What is the value of the multiple correlation (that is, the correlation between the dependent variable and the set of independent variables)?
B) What is the value of the coefficient of determination?
C) Of the two independent variables, which has the stronger net effect on the dependent variable?
D) Write out the regression equation. (You may use Y and X's in the regression equation or, in place of the Y and X's, you may use variable names.)

Accepted Answer

a. .323
b. .104
c. S

Question 19

Which independent variable has the strongest net effect on GPA?

Accepted Answer

A)  SAT 
B)  HSRank 
C)  BIRTH 
A)  SAT 
B)  HSRank 
C)  BIRTH

What types of dependent variables are ok to use for linear regression?

What proportion of the differences in the dependent variable is explained by the independent variables in the regression equation?

If you want to see which factor (age at marriage, educational level, or income) had the strongest net effect on marital happiness, what is an appropriate statistical technique to use?

In the context of regression analysis, each of the following has at least one other name. State at least one of those other names:

If you want to see what the cases in your data set are like on a single continuous, interval/ratio variable, what is an appropriate statistical technique to use?

The regression equation is Y = 50 - 5X₁ + 10X₂ - 20X₃. A case has a value of 1 on X₁, 2 on X₂, and 3 on X₃. What's the predicted value?

According to the following regression equation: INCOME = 9000 + 2500(EDUC) − 100(AGE) − 5000(FEMALE), an increase of one year in education results in how much of a change in income? (State both the amount of change and the direction.)

When would you use Crosstabs to look at the net effects of two independent variables on a dependent variable and when would you use Linear Regression?

If you want to see the net effect of gender on academic achievement after controlling for age and parents' social class, what is an appropriate statistical technique to use?

What is multicollinearity and why is it a problem?

Let's say the correlation between SAT scores and college GPA is .70 but when you regress college GPA on SAT scores and parents' social class, the standardized coefficient for SAT scores is .02. What would this tell you?

If you want to see how well percent of classes attended and percent of assigned reading completed do together in accounting for differences in student exam grades, what is an appropriate statistical technique to use?

What kinds of questions can you answer using multiple regression?

The regression equation is POVERTY = 10 + 1(UNEMPLOYMENT) - 0.5(COLLEGE). A county has a POVERTY rate of 30, an UNEMPLOYMENT rate of 10, and COLLEGE graduate rate of 10. What is the county's regression residual?

What is a net effect?

Which independent variable has the strongest net effect on GPA?

Introduction

Data Sets

Frequency Tables and Univariate Charts

Central Tendency and Dispersion

Creating New Variables

Comparing Group Means

Crosstab Tables

Nominal and Ordinal Measures of Association

Pearsons Correlation and Bivariate Regression

Sampling Distributions and Normal Distributions

Hypothesis Testing and One-Sample T Tests

Paired and Independent-Samples T Tests

Analysis of Variance

Chi-Square

Hypothesis Testing With Measures of Association and Regression

Filters

Exam 10: Multiple Regression

What types of dependent variables are ok to use for linear regression?

What proportion of the differences in the dependent variable is explained by the independent variables in the regression equation?

If you want to see which factor (age at marriage, educational level, or income) had the strongest net effect on marital happiness, what is an appropriate statistical technique to use?

In the context of regression analysis, each of the following has at least one other name. State at least one of those other names:

If you want to see what the cases in your data set are like on a single continuous, interval/ratio variable, what is an appropriate statistical technique to use?

The regression equation is Y = 50 - 5X1 + 10X2 - 20X3. A case has a value of 1 on X1, 2 on X2, and 3 on X3. What's the predicted value?

According to the following regression equation: INCOME = 9000 + 2500(EDUC) − 100(AGE) − 5000(FEMALE), an increase of one year in education results in how much of a change in income? (State both the amount of change and the direction.)

When would you use Crosstabs to look at the net effects of two independent variables on a dependent variable and when would you use Linear Regression?

If you want to see the net effect of gender on academic achievement after controlling for age and parents' social class, what is an appropriate statistical technique to use?

What is multicollinearity and why is it a problem?

Let's say the correlation between SAT scores and college GPA is .70 but when you regress college GPA on SAT scores and parents' social class, the standardized coefficient for SAT scores is .02. What would this tell you?

If you want to see how well percent of classes attended and percent of assigned reading completed do together in accounting for differences in student exam grades, what is an appropriate statistical technique to use?

What kinds of questions can you answer using multiple regression?

The regression equation is POVERTY = 10 + 1(UNEMPLOYMENT) - 0.5(COLLEGE). A county has a POVERTY rate of 30, an UNEMPLOYMENT rate of 10, and COLLEGE graduate rate of 10. What is the county's regression residual?

What is a net effect?

Which independent variable has the strongest net effect on GPA?

Introduction

Data Sets

Frequency Tables and Univariate Charts

Central Tendency and Dispersion

Creating New Variables

Comparing Group Means

Crosstab Tables

Nominal and Ordinal Measures of Association

Pearsons Correlation and Bivariate Regression

Sampling Distributions and Normal Distributions

Hypothesis Testing and One-Sample T Tests

Paired and Independent-Samples T Tests

Analysis of Variance

Chi-Square

Hypothesis Testing With Measures of Association and Regression

Filters

The regression equation is Y = 50 - 5X₁ + 10X₂ - 20X₃. A case has a value of 1 on X₁, 2 on X₂, and 3 on X₃. What's the predicted value?