Question 1

What must be used to examine an outcome that is predicted from two independent variables?

Accepted Answer

A) multivariate regression 
B) multiple regression 
C) simple regression 
D) complicated regression 
A) multivariate regression 
B) multiple regression 
C) simple regression 
D) complicated regression

Question 2

Using the regression formula with a slope = .704 and an intercept = .719, what would the predicted college GPA be for a student whose current high school GPA = 3.2?

Accepted Answer

A) 2.69 
B) 2.97 
C) 3.00 
D) 3.20 
A) 2.69 
B) 2.97 
C) 3.00 
D) 3.20

Question 3

Using the regression formula with a slope = .704 and an intercept = .319, what would the predicted college GPA be for a student whose current high school GPA = 3.2?

Accepted Answer

A) 2.57 
B) 2.33 
C) 3.61 
D) 3.20 
A) 2.57 
B) 2.33 
C) 3.61 
D) 3.20

Question 4

A perfect correlation would translate into perfect prediction in the case of linear regression.

Accepted Answer

A) True 
 B)False

Question 5

The standard error of estimate tells you how much imprecision there is overall in regard to the predictive power of the linear regression analysis.

Accepted Answer

A) True 
 B)False

Question 6

Based on the formula for a regression line, what does b represent?

Accepted Answer

A) known value of X 
B) slope of a line 
C) y-intercept 
D) predictor score 
A) known value of X 
B) slope of a line 
C) y-intercept 
D) predictor score

Question 7

More accurate predictions are associated with ______.

Accepted Answer

A) correlations having higher absolute values 
B) correlations having lower absolute values 
C) correlations having higher values 
D) correlations having lower values 
A) correlations having higher absolute values 
B) correlations having lower absolute values 
C) correlations having higher values 
D) correlations having lower values

Question 8

Simple linear regression consists of a type of regression in which more than one independent variable is included in the analysis.

Accepted Answer

A) True 
 B)False

Question 9

In multiple regression, added variables must be related to the outcome variable but ______.

Accepted Answer

A) correlated with and unrelated to each other 
B) independent of and correlated with each other 
C) independent of and uncorrelated with each other 
D) dependent of and uncorrelated with each other 
A) correlated with and unrelated to each other 
B) independent of and correlated with each other 
C) independent of and uncorrelated with each other 
D) dependent of and uncorrelated with each other

Question 10

Using the regression formula with a slope = .904 and an intercept = .719, what would the predicted college GPA be for a student whose current high school GPA = 3.2?

Accepted Answer

A) 2.69 
B) 2.33 
C) 3.61 
D) 3.20 
A) 2.69 
B) 2.33 
C) 3.61 
D) 3.20

Question 11

If the absolute value of your correlation is 0.9, your error in prediction will be ______.

Accepted Answer

A) high 
B) low 
C) very low 
D) 0 
A) high 
B) low 
C) very low 
D) 0

Question 12

Using the regression formula with a slope = 2,000 and an intercept = 15,000, what would the predicted income be for someone who has 5 years of education?

Accepted Answer

A) $25,000 
B) $42,000 
C) $45,000 
D) $47,000 
A) $25,000 
B) $42,000 
C) $45,000 
D) $47,000

Question 13

Using the regression formula with a slope = .704 and an intercept = .919, what would the predicted college GPA be for a student whose current high school GPA = 3.2?

Accepted Answer

A) 2.69 
B) 2.97 
C) 3.00 
D) 3.17 
A) 2.69 
B) 2.97 
C) 3.00 
D) 3.17

Question 14

When computing a predicted value, you first ______.

Accepted Answer

A) add the slope to the value of the independent variable 
B) multiply the slope by the value of the independent variable 
C) add the constant to the value of the independent variable 
D) subtract the constant from the value of the independent variable 
A) add the slope to the value of the independent variable 
B) multiply the slope by the value of the independent variable 
C) add the constant to the value of the independent variable 
D) subtract the constant from the value of the independent variable

Question 15

Using the regression formula with a slope = .704 and an intercept = .719, what would the predicted college GPA be for a student whose current high school GPA = 4.2?

Accepted Answer

A) 3.68 
B) 2.97 
C) 3.00 
D) 3.20 
A) 3.68 
B) 2.97 
C) 3.00 
D) 3.20

Question 16

When adding additional predictors to a regression analysis, you should try to find predictors that are related to _______ but not _______.

Accepted Answer

A) the independent variable; the dependent variables 
B) the dependent variable; the independent variables 
C) the predictors; the outcome 
D) all main effects; any interaction effect 
A) the independent variable; the dependent variables 
B) the dependent variable; the independent variables 
C) the predictors; the outcome 
D) all main effects; any interaction effect

Question 17

What does a unique contribution mean for a variable?

Accepted Answer

A unique contribution means th

Question 18

Not all lines that are the best fit for a bunch of data points are straight.Rather, they could be _______.

Accepted Answer

A) linear 
B) invalid 
C) curvilinear 
D) parallel-linear 
A) linear 
B) invalid 
C) curvilinear 
D) parallel-linear

Question 19

If the absolute value of your correlation is 0.1 your error in prediction will be ______.

Accepted Answer

A) high 
B) low 
C) very low 
D) 0 
A) high 
B) low 
C) very low 
D) 0

Question 20

The general formula for a regression line is _______.

Accepted Answer

A) a² + b² = c² 
B) aX + b = Y 
C) bX + a = 
D) dX + a = 
A) a² + b² = c² 
B) aX + b = Y 
C) bX + a = 
D) dX + a =

Exam 16: Predicting Wholl Win the Super Bowl: Using Linear Regression

What must be used to examine an outcome that is predicted from two independent variables?

Using the regression formula with a slope = .704 and an intercept = .719, what would the predicted college GPA be for a student whose current high school GPA = 3.2?

Using the regression formula with a slope = .704 and an intercept = .319, what would the predicted college GPA be for a student whose current high school GPA = 3.2?

A perfect correlation would translate into perfect prediction in the case of linear regression.

The standard error of estimate tells you how much imprecision there is overall in regard to the predictive power of the linear regression analysis.

Based on the formula for a regression line, what does b represent?

More accurate predictions are associated with ______.

Simple linear regression consists of a type of regression in which more than one independent variable is included in the analysis.

In multiple regression, added variables must be related to the outcome variable but ______.

Using the regression formula with a slope = .904 and an intercept = .719, what would the predicted college GPA be for a student whose current high school GPA = 3.2?

If the absolute value of your correlation is 0.9, your error in prediction will be ______.

Using the regression formula with a slope = 2,000 and an intercept = 15,000, what would the predicted income be for someone who has 5 years of education?

Using the regression formula with a slope = .704 and an intercept = .919, what would the predicted college GPA be for a student whose current high school GPA = 3.2?

When computing a predicted value, you first ______.

Using the regression formula with a slope = .704 and an intercept = .719, what would the predicted college GPA be for a student whose current high school GPA = 4.2?

When adding additional predictors to a regression analysis, you should try to find predictors that are related to _______ but not _______.

What does a unique contribution mean for a variable?

Not all lines that are the best fit for a bunch of data points are straight.Rather, they could be _______.

If the absolute value of your correlation is 0.1 your error in prediction will be ______.

The general formula for a regression line is _______.

Statistics or Sadistics Its up to You

Means to an End: Computing and Understanding Averages

Vive La Différence: Understanding Variability

A Picture Really Is Worth a Thousand Words

Ice Cream and Crime: Computing Correlation Coefficients

Just the Truth: An Introduction to Understanding Reliability and Validity

Hypotheticals and You: Testing Your Questions

Are Your Curves Normal Probability and Why It Counts

Significantly Significant: What It Means for You and Me

Only the Lonely: The One Sample Z-Test

Tea for Two: Tests Between the Means of Different Groups

Tea for Two Again: Tests Between the Means of Related Groups

Two Groups Too Many Try Analysis of Variance

Two Too Many Factors: Factorial Analysis of Variancea Brief Introduction

Cousins or Just Good Friends Testing Relationships Using Correlation Coefficient

What to Do When Youre Not Normal: CHI-Square and Some Other Nonparametric Tests

Some Other Important Statistical Procedures You Should Know About

Data Mining: An Introduction to Getting the Most Out of Your Big Data

A Statistical Software Sampler

The Ten or More Best and Most Fun Internet Sites for Statistics Stuff

The Ten Commandments of Data Collection

Filters

When adding additional predictors to a regression analysis, you should try to find predictors that are related to _ but not _.