Question 1

A correlation of -.88 between television viewing time and grades in high school is best understood as demonstrating that

Accepted Answer

A)  as television viewing time increases, grades increase 
B)  as television viewing time decreases, grades decrease 
C)  as television viewing time increases, grades decrease. 
A)  as television viewing time increases, grades increase 
B)  as television viewing time decreases, grades decrease 
C)  as television viewing time increases, grades decrease.

Question 2

Galton's effort to find ways to improve the human condition led him to study the field of

Accepted Answer

A)  psychology 
B)  physics 
C)  physiology 
D)  heredity. 
A)  psychology 
B)  physics 
C)  physiology 
D)  heredity.

Question 3

Data Set 6-1
The correlation between the number of PhDs and the number of mules in a state used to be approximately -.90. Accept the following simplified summary data.
 $\begin{array}{lll}
& \underline{\text { PhDs}}& \underline{\text { Mules }}\
\text { Mean } & 40 & 200 \
\text { Standard Deviation } & 15 & 50
\end{array}$ 
In questions based on Data Set 6-1, the task is to predict the number of mules for a state, given the number of PhDs.
-Look at Data Set 6-1. For a state with 60 PhDs the predicted number of mules would be

Accepted Answer

A)  260 
B)  195 
C)  140 
D)  none of the other alternatives are correct. 
A)  260 
B)  195 
C)  140 
D)  none of the other alternatives are correct.

Question 4

A ___ correlation coefficient indicates a medium effect size according to Cohen; a ___ correlation coefficient indicates a reliable measuring instrument.

Accepted Answer

A)  .30 .60 
B)  .10 .50 
C)  .30 .80 
D)  .50 50. 
A)  .30 .60 
B)  .10 .50 
C)  .30 .80 
D)  .50 50.

Question 5

From the data below, $$\begin{array} { r c } 
 \underline{\text { IQ } } &  \underline{\text { Self-esteem Score }} \
100 & 5 \
90 & 5 \
120 & 4 \
130 & 6 \
110 & 7
\end{array}$$ 
a. draw a scatterplot.
b. compute r.
c. with self-esteem as Y, calculate the regression coefficients.
d. interpret the r value you have computed.

Accepted Answer

a.
 @#IMG-DLM& b.
\[\begin{array} { c c c } 
\Sigm

Question 6

Error in a regression analysis is defined as

Accepted Answer

A)  $\hat { Y }$ 
B)  Y - $\hat { Y }$ 
C)  $\hat { Y }$ - Y 
D)  (Y - $\hat { Y }$ )2 
A)  $\hat { Y }$ 
B)  Y - $\hat { Y }$ 
C)  $\hat { Y }$ - Y 
D)  (Y - $\hat { Y }$ )2

Question 7

Given the regression equation, $\hat { Y }$ = 10 + 3X, where X is a personality score and $\hat { Y }$ is a "success"score, what success score would be predicted for a person whose personality score was 31?

Accepted Answer

A)  100 
B)  7 
C)  neither 100 nor 7 
D)  cannot be determined from the information given. 
A)  100 
B)  7 
C)  neither 100 nor 7 
D)  cannot be determined from the information given.

Question 8

In a bivariate distribution

Accepted Answer

A)  there is always a pairing of every score in one distribution with another score in the other distribution 
B)  both distributions use the same units of measurement 
C)  both descriptive alternative are correct 
D)  neither of the descriptive alternatives is correct. 
A)  there is always a pairing of every score in one distribution with another score in the other distribution 
B)  both distributions use the same units of measurement 
C)  both descriptive alternative are correct 
D)  neither of the descriptive alternatives is correct.

Question 9

Given the regression equation, $\hat { Y }$ = 3 + 2X, where X is a score on a test of simple algebra and $\hat { Y }$ is a score on a college statistics exam, what statistics exam score would you predict for an algebra score of 12?

Accepted Answer

A)  60 
B)  28 
C)  27 
D)  cannot be determined from the information given. 
A)  60 
B)  28 
C)  27 
D)  cannot be determined from the information given.

Question 10

The number of regression lines for a bivariate distribution is equal to the number of regression coefficients.

Accepted Answer

A) True 
 B)False

Question 11

The numerator of the definitional formula of the correlation coefficient is the product of the two regression coefficients.

Accepted Answer

A) True 
 B)False

Question 12

In a bivariate distribution

Accepted Answer

A)  both variables must be measuring the same thing 
B)  both variables have the same number of scores 
C)  there are exactly two scores 
D)  all of the other alternatives are correct. 
A)  both variables must be measuring the same thing 
B)  both variables have the same number of scores 
C)  there are exactly two scores 
D)  all of the other alternatives are correct.

Question 13

Suppose you had a correlation coefficient calculated on data from variables that were not linearly related. Such a coefficient

Accepted Answer

A)  probably overstates the strength of the relationship 
B)  is an accurate reflection of the strength of the relationship 
C)  is not based on bivariate data 
D)  is not the appropriate way to describe the strength of the relationship. 
A)  probably overstates the strength of the relationship 
B)  is an accurate reflection of the strength of the relationship 
C)  is not based on bivariate data 
D)  is not the appropriate way to describe the strength of the relationship.

Question 14

Correlation coefficients can be used to establish

Accepted Answer

A)  variance in common 
B)  reliability 
C)  both variance in common and reliability 
D)  neither variance in common nor reliability. 
A)  variance in common 
B)  reliability 
C)  both variance in common and reliability 
D)  neither variance in common nor reliability.

Question 15

Depending on the units chosen for the X and Y axis,

Accepted Answer

A)  the regression line may cross the Y axis at a point other than a 
B)  the slope may appear to be steeper or more shallow than b 
C)  both descriptive alternatives are correct 
D)  neither of the descriptive alternatives is correct. 
A)  the regression line may cross the Y axis at a point other than a 
B)  the slope may appear to be steeper or more shallow than b 
C)  both descriptive alternatives are correct 
D)  neither of the descriptive alternatives is correct.

Question 16

Correlation coefficients can approach 1.00 but never reach that value.

Accepted Answer

A) True 
 B)False

Question 17

If a bivariate distribution is not linear, r will not show the degree of relationship between two variables.

Accepted Answer

A) True 
 B)False

Question 18

The correlation between per capita income and violent crime rate in the 50 American states is

Accepted Answer

A)  about zero 
B)  close to .75 
C)  close to -.75 
D)  between -.25 and .25. 
A)  about zero 
B)  close to .75 
C)  close to -.75 
D)  between -.25 and .25.

Question 19

The sum of the cross-products is

Accepted Answer

A)  $\Sigma$X+ $\Sigma$Y 
B)  ($\Sigma$X) ($\Sigma$Y) 
C)  both descriptive alternatives are correct 
D)  neither of the descriptive alternatives is correct. 
A)  $\Sigma$X+ $\Sigma$Y 
B)  ($\Sigma$X) ($\Sigma$Y) 
C)  both descriptive alternatives are correct 
D)  neither of the descriptive alternatives is correct.

Question 20

Situation A: correlation coefficient of .00; Situation B; correlation coefficient of 1.00. With respect to cause and effect statements, Situation A allows the statement  and Situation B allows .

Accepted Answer

A)  "there is no cause and effect relationship" and "there is no cause and effect relationship" 
B)  "there is no cause and effect relationship" and "there may be a cause and effect relationship" 
C)  "there may be a cause and effect relationship" and "there may be a cause and effect relationship." 
A)  "there is no cause and effect relationship" and "there is no cause and effect relationship" 
B)  "there is no cause and effect relationship" and "there may be a cause and effect relationship" 
C)  "there may be a cause and effect relationship" and "there may be a cause and effect relationship."

A correlation of -.88 between television viewing time and grades in high school is best understood as demonstrating that

Galton's effort to find ways to improve the human condition led him to study the field of

A _ correlation coefficient indicates a medium effect size according to Cohen; a _ correlation coefficient indicates a reliable measuring instrument.

From the data below, 100 5 90 5 120 4 130 6 110 7 a. draw a scatterplot. b. compute r. c. with self-esteem as Y, calculate the regression coefficients. d. interpret the r value you have computed.

Error in a regression analysis is defined as

Given the regression equation, $\hat { Y }$ = 10 + 3X, where X is a personality score and $\hat { Y }$ is a "success"score, what success score would be predicted for a person whose personality score was 31?

In a bivariate distribution

Given the regression equation, $\hat { Y }$ = 3 + 2X, where X is a score on a test of simple algebra and $\hat { Y }$ is a score on a college statistics exam, what statistics exam score would you predict for an algebra score of 12?

The number of regression lines for a bivariate distribution is equal to the number of regression coefficients.

The numerator of the definitional formula of the correlation coefficient is the product of the two regression coefficients.

In a bivariate distribution

Suppose you had a correlation coefficient calculated on data from variables that were not linearly related. Such a coefficient

Correlation coefficients can be used to establish

Depending on the units chosen for the X and Y axis,

Correlation coefficients can approach 1.00 but never reach that value.

If a bivariate distribution is not linear, r will not show the degree of relationship between two variables.

The correlation between per capita income and violent crime rate in the 50 American states is

The sum of the cross-products is

Situation A: correlation coefficient of .00; Situation B; correlation coefficient of 1.00. With respect to cause and effect statements, Situation A allows the statement and Situation B allows .

Introduction

Exploring Data: Frequency Distributions and Graphs

Exploring Data: Central Tendency

Exploring Data: Variability

Other Descriptive Statistics

Theoretical Distributions Including the Normal Distribution

Samples, Sampling Distributions, and Confidence Intervals

Hypothesis Testing and Effect Size: One-Sample Designs

Hypothesis Testing, Effect Size, and and Confidence Intervals: Two-Sample Designs

Analysis of Variance: One-Way Classification

Analysis of Variance: One-Factor Repeated Measures

Analysis of Variance: Factorial Design

Chi Square Tests

More Nonparametric Tests

Appendix: Grouped Frequency Distributions and Central Tendency

Filters

Exam 6: Correlation and Regression

A correlation of -.88 between television viewing time and grades in high school is best understood as demonstrating that

Galton's effort to find ways to improve the human condition led him to study the field of

A ___ correlation coefficient indicates a medium effect size according to Cohen; a ___ correlation coefficient indicates a reliable measuring instrument.

From the data below, 100 5 90 5 120 4 130 6 110 7 a. draw a scatterplot. b. compute r. c. with self-esteem as Y, calculate the regression coefficients. d. interpret the r value you have computed.

Error in a regression analysis is defined as

Given the regression equation, Y^\hat { Y }Y^ = 10 + 3X, where X is a personality score and Y^\hat { Y }Y^ is a "success"score, what success score would be predicted for a person whose personality score was 31?

In a bivariate distribution

Given the regression equation, Y^\hat { Y }Y^ = 3 + 2X, where X is a score on a test of simple algebra and Y^\hat { Y }Y^ is a score on a college statistics exam, what statistics exam score would you predict for an algebra score of 12?

The number of regression lines for a bivariate distribution is equal to the number of regression coefficients.

The numerator of the definitional formula of the correlation coefficient is the product of the two regression coefficients.

In a bivariate distribution

Suppose you had a correlation coefficient calculated on data from variables that were not linearly related. Such a coefficient

Correlation coefficients can be used to establish

Depending on the units chosen for the X and Y axis,

Correlation coefficients can approach 1.00 but never reach that value.

If a bivariate distribution is not linear, r will not show the degree of relationship between two variables.

The correlation between per capita income and violent crime rate in the 50 American states is

The sum of the cross-products is

Situation A: correlation coefficient of .00; Situation B; correlation coefficient of 1.00. With respect to cause and effect statements, Situation A allows the statement and Situation B allows .

Introduction

Exploring Data: Frequency Distributions and Graphs

Exploring Data: Central Tendency

Exploring Data: Variability

Other Descriptive Statistics

Theoretical Distributions Including the Normal Distribution

Samples, Sampling Distributions, and Confidence Intervals

Hypothesis Testing and Effect Size: One-Sample Designs

Hypothesis Testing, Effect Size, and and Confidence Intervals: Two-Sample Designs

Analysis of Variance: One-Way Classification

Analysis of Variance: One-Factor Repeated Measures

Analysis of Variance: Factorial Design

Chi Square Tests

More Nonparametric Tests

Appendix: Grouped Frequency Distributions and Central Tendency

Filters

A _ correlation coefficient indicates a medium effect size according to Cohen; a _ correlation coefficient indicates a reliable measuring instrument.

Given the regression equation, $\hat { Y }$ = 10 + 3X, where X is a personality score and $\hat { Y }$ is a "success"score, what success score would be predicted for a person whose personality score was 31?

Given the regression equation, $\hat { Y }$ = 3 + 2X, where X is a score on a test of simple algebra and $\hat { Y }$ is a score on a college statistics exam, what statistics exam score would you predict for an algebra score of 12?