Question 1

If the correlation coefficient between two quantitative variables is positive, what conclusion can we draw?

Accepted Answer

A)  High values on the first variable are associated with high values on the second variable. 
B)  Low values on the first variable are associated with low values on the second variable. 
C)  High values on the first variable are associated with low values on the second variable. 
D)  Both A and B are correct. 
A)  High values on the first variable are associated with high values on the second variable. 
B)  Low values on the first variable are associated with low values on the second variable. 
C)  High values on the first variable are associated with low values on the second variable. 
D)  Both A and B are correct.

Question 2

Describe the type of association shown in the scatterplot below:

Accepted Answer

A)  Positive linear association 
B)  Negative linear association 
C)  Positive curvilinear association 
D)  Negative curvilinear association 
A)  Positive linear association 
B)  Negative linear association 
C)  Positive curvilinear association 
D)  Negative curvilinear association

Question 3

Use the following information for questions:
 A group of adults aged 20 to 80 were tested to see how far away they could first hear an ambulance coming towards them. An equation describing the relationship between distance (in feet) and age was found to be:
Distance = 600 - 3 * Age.
-Based on the equation, what is the direction of the association between distance and age?

Accepted Answer

A)  Positive 
B)  Negative 
C)  Zero 
D)  Direction can't be determined from the equation. 
A)  Positive 
B)  Negative 
C)  Zero 
D)  Direction can't be determined from the equation.

Question 4

Describe the type of association shown in the scatterplot below:

Accepted Answer

A)  Positive linear association 
B)  Negative linear association 
C)  Positive curvilinear association 
D)  Negative curvilinear association 
A)  Positive linear association 
B)  Negative linear association 
C)  Positive curvilinear association 
D)  Negative curvilinear association

Question 5

A car salesman is curious if he can predict the fuel efficiency of a car (in MPG) if he knows the fuel capacity of the car (in gallons). He collects data on a variety of makes and models of cars. The scatterplot below shows the association between fuel capacity and fuel efficiency for a sample of 78 cars. Is the association negative or positive? Linear or curvilinear? Are there any outliers?

Accepted Answer

There is a negative association, which m

Question 6

Use the following information for questions:
 The 25 item "Parenting Hassles Scale" asks parents questions about certain situations in their family. They are asked to rate these situations on (1) how often they occur (frequency), and (2) how much they bother them (intensity). The score system for the frequency was 0-4 points (0 = never, 4 = all the time) and for the intensity 1-5 (1 = not much at all, 5 = very much). If an item received a 0 (zero) for frequency, it automatically received a 0 (zero) for intensity. The two variables, frequency and intensity, were formed by taking the total of the corresponding scores from the two rating scales across the various situations. In a scatterplot, these two variables showed an approximate linear relationship. They were then used to run a linear regression to predict intensity based on frequency.
    
-What is an estimate for the average intensity score for parents who score 33 on the frequency scale?

Accepted Answer

The answer of Use the following information for questions:
 The...

Question 7

Use the following information for questions:
 A regression was done for 20 cities with latitude as the explanatory variable (x) and average January temperature as the response variable (y). The latitude is measured in degrees and average January temperature in degrees Fahrenheit. The latitudes ranged from 26 (Miami) to 47 (Duluth) The regression equation is $\hat{y}$ = 49.4 - 0.313x.
-The total sum of squares (SSTO) = 4436.6, and the error sum of squares (SSE) = 1185.8. What is the value of r2 the proportion of variation in y explained by its linear relationship with x?

Accepted Answer

(4426.6 -

Question 8

A scatter plot of number of teachers and number of people with college degrees for cities in Pennsylvania reveals a positive association. The most likely explanation for this positive association is:

Accepted Answer

A)  Teachers encourage people to get college degrees, so an increase in the number of teachers is causing an increase in the number of people with college degrees. 
B)  Teaching is a common profession for people with college degrees, so an increase in the number of people with college degrees causes an increase in the number of teachers. 
C)  Cities with higher incomes tend to have more teachers and more people going to college, so income is a confounding variable, making causation between number of teachers and number of people with college degrees difficult to prove. 
D)  Larger cities tend to have both more teachers and more people with college degrees, so the association is explained by a third variable, the size of the city. 
A)  Teachers encourage people to get college degrees, so an increase in the number of teachers is causing an increase in the number of people with college degrees. 
B)  Teaching is a common profession for people with college degrees, so an increase in the number of people with college degrees causes an increase in the number of teachers. 
C)  Cities with higher incomes tend to have more teachers and more people going to college, so income is a confounding variable, making causation between number of teachers and number of people with college degrees difficult to prove. 
D)  Larger cities tend to have both more teachers and more people with college degrees, so the association is explained by a third variable, the size of the city.

Question 9

Use the following information for questions:
 A graduate student is doing a research project on stress among recent immigrants. She focused on parents of young children. All parents answered questions on a questionnaire (with the help of a translator if necessary). A stress score was calculated for all participants. SPSS was used to run a simple linear regression in which y = stress of the parent and x = age of the parent.
    
-What is an estimate for the average stress score for parents who are 28 years old?

Accepted Answer

A)  2.114 
B)  67.805 
C)  15.918 
D)  27.692 
A)  2.114 
B)  67.805 
C)  15.918 
D)  27.692

Question 10

Use the following information for questions:
 The next three questions are based on a regression equation for 55 college students with x = left forearm length (cm) and y = height. The forearm lengths ranged from 22 cm to 31 cm. The regression equation is $\hat{y}$ = 30.3 + 1.49x
-One student's left forearm length was 27 cm, and his height was 75 inches. What is the estimated height for this student, based on the regression equation? What is the residual?

Accepted Answer

The estimated height

Question 11

Use the following information for questions:
 A regression between foot length (response variable in cm) and height (explanatory variable in inches) for 33 students resulted in the following regression equation: $\hat{y}$ = 10.9 + 0.23x
-One student in the sample was 73 inches tall with a foot length of 29 cm. What is the residual for this student?

Accepted Answer

A)  29 cm 
B)  1.31 cm 
C)  0.00 cm 
D)  -1.31 cm 
A)  29 cm 
B)  1.31 cm 
C)  0.00 cm 
D)  -1.31 cm

Question 12

Which one of the following statements involving correlation is possible and reasonable?

Accepted Answer

A)  The correlation between hair color and eye color is 0.80. 
B)  The correlation between the height of a father and the height of his first son is 0.6 
C)  The correlation between left foot length and right foot length is 2.35. 
D)  The correlation between hair color and age is positive. 
A)  The correlation between hair color and eye color is 0.80. 
B)  The correlation between the height of a father and the height of his first son is 0.6 
C)  The correlation between left foot length and right foot length is 2.35. 
D)  The correlation between hair color and age is positive.

Question 13

Use the following information for questions:
 The next three questions are based on a regression equation for 55 college students with x = left forearm length (cm) and y = height. The forearm lengths ranged from 22 cm to 31 cm. The regression equation is $\hat{y}$ = 30.3 + 1.49x
-The instructor's left forearm length is 35 cm. Is there any problem with using the regression equation to estimate the instructor's height?

Accepted Answer

The instructor's left forearm

Question 14

Use the following information for questions:
 Consider the following scatterplots for two quantitative variables y and x. One point has been labeled in each plot.
  
-Which point would produce the largest residual?

Accepted Answer

A)  Point A 
B)  Point B 
A)  Point A 
B)  Point B

Question 15

Use the following information for questions:
 A regression was done for 20 cities with latitude as the explanatory variable (x) and average January temperature as the response variable (y). The latitude is measured in degrees and average January temperature in degrees Fahrenheit. The latitudes ranged from 26 (Miami) to 47 (Duluth) The regression equation is $\hat{y}$ = 49.4 - 0.313x
-The city of Pittsburgh, PA has latitude 40 degrees with average January temperature of 25 degrees Fahrenheit. What is the estimated average January temperature for Pittsburgh, based on the regression equation? What is the residual?

Accepted Answer

The estimated Januar

Question 16

The 25 item "Parenting Hassles Scale" asks parents questions about certain situations in their family. They are asked to rate these situations on (1) how often they occur (frequency), and (2) how much they bother them (intensity). The score system for the frequency was 0-4 points (0 = never, 4 = all the time) and for the intensity 1-5 (1 = not much at all, 5 = very much). If an item received a 0 (zero) for frequency, it automatically received a 0 (zero) for intensity. The two variables, frequency and intensity, were formed by taking the total of the corresponding scores from the two rating scales across the various situations These two variables are then used to create a scatterplot. The symbols indicate whether a mother, a father, or a step parent filled in the questionnaire.
   Based on the scatterplot, what is the problem with using one regression equation for all parents combined?

Accepted Answer

It appears that the stepparents and biol

Question 17

Which of the following can not be answered from a regression equation?

Accepted Answer

A)  Predict the value of y at a particular value of x. 
B)  Estimate the slope between y and x. 
C)  Estimate whether the linear association is positive or negative. 
D)  Estimate whether the association is linear or non-linear 
A)  Predict the value of y at a particular value of x. 
B)  Estimate the slope between y and x. 
C)  Estimate whether the linear association is positive or negative. 
D)  Estimate whether the association is linear or non-linear

Question 18

Which of the following is a possible value of r2, and indicates the strongest linear relationship between two quantitative variables?

Accepted Answer

A)  -90% 
B)  0% 
C)  80% 
D)  120%. 
A)  -90% 
B)  0% 
C)  80% 
D)  120%.

Question 19

What is the effect of an outlier on the value of a correlation coefficient?

Accepted Answer

A)  An outlier will always decrease a correlation coefficient. 
B)  An outlier will always increase a correlation coefficient. 
C)  An outlier might either decrease or increase a correlation coefficient, depending on where it is in relation to the other points. 
D)  An outlier will have no effect on a correlation coefficient. 
A)  An outlier will always decrease a correlation coefficient. 
B)  An outlier will always increase a correlation coefficient. 
C)  An outlier might either decrease or increase a correlation coefficient, depending on where it is in relation to the other points. 
D)  An outlier will have no effect on a correlation coefficient.

If the correlation coefficient between two quantitative variables is positive, what conclusion can we draw?

Describe the type of association shown in the scatterplot below:

Describe the type of association shown in the scatterplot below:

A scatter plot of number of teachers and number of people with college degrees for cities in Pennsylvania reveals a positive association. The most likely explanation for this positive association is:

Which one of the following statements involving correlation is possible and reasonable?

Use the following information for questions: Consider the following scatterplots for two quantitative variables y and x. One point has been labeled in each plot. -Which point would produce the largest residual?

Which of the following can not be answered from a regression equation?

Which of the following is a possible value of r², and indicates the strongest linear relationship between two quantitative variables?

What is the effect of an outlier on the value of a correlation coefficient?

Statistics Success Stories and Cautionary Tales

Turning Data Into Information

Relationships Between Categorical Variables

Sampling: Surveys and How to Ask Questions

Gathering Useful Data for Examining Relationships

Probability

Random Variables

Understanding Sampling Distributions: Statistics As Random Variables

Estimating Proportions With Confidence

Estimating Means With Confidence

Testing Hypotheses About Proportions

Testing Hypotheses About Means

Inference About Simple Regression

More About Inference for Categorical Variables

Analysis of Variance

Turning Information Into Wisdom

Filters

Exam 3: Relationships Between Quantitative Variables

If the correlation coefficient between two quantitative variables is positive, what conclusion can we draw?

Describe the type of association shown in the scatterplot below:

Describe the type of association shown in the scatterplot below:

A scatter plot of number of teachers and number of people with college degrees for cities in Pennsylvania reveals a positive association. The most likely explanation for this positive association is:

Which one of the following statements involving correlation is possible and reasonable?

Use the following information for questions: Consider the following scatterplots for two quantitative variables y and x. One point has been labeled in each plot. -Which point would produce the largest residual?

Which of the following can not be answered from a regression equation?

Which of the following is a possible value of r2, and indicates the strongest linear relationship between two quantitative variables?

What is the effect of an outlier on the value of a correlation coefficient?

Statistics Success Stories and Cautionary Tales

Turning Data Into Information

Relationships Between Categorical Variables

Sampling: Surveys and How to Ask Questions

Gathering Useful Data for Examining Relationships

Probability

Random Variables

Understanding Sampling Distributions: Statistics As Random Variables

Estimating Proportions With Confidence

Estimating Means With Confidence

Testing Hypotheses About Proportions

Testing Hypotheses About Means

Inference About Simple Regression

More About Inference for Categorical Variables

Analysis of Variance

Turning Information Into Wisdom

Filters

Which of the following is a possible value of r², and indicates the strongest linear relationship between two quantitative variables?