1.	An outlier is an individual value that	
A)	extends the pattern.	
B)	deviates from the pattern.	
C)	determines the strength of the relationship.	
D)	outlines the general form of the data.	

2.	If two variables are negatively associated, then above-average values of one tend to accompany	
A)	below average values of the other.	C)	oppositely signed values of the other.	
B)	above average values of the other.	D)	negatively signed values of the other.	

3.	If two variables are both positive, and tend to be linked so that growth of one variable tends to indicate growth in the other variable, then	
A)	the variables are positively associated.	
B)	the variables are negatively associated.	
C)	the variables have no association with each other.	

4.	If a regression line for two variables has a small positive slope, then	
A)	the variables are positively associated.	
B)	the variables are negatively associated.	
C)	the association of the variables cannot be determined.	
D)	the variables have no association with each other.	

5.	If two variables are negatively associated, then the regression line	
A)	has a negative intercept.	C)	has negative coefficients.	
B)	has a negative slope.	D)	is valid for only negative values.	

6.	If two variables are positively associated, then the regression line	
A)	is horizontal.	C)	has a positive slope.	
B)	has a positive intercept.	D)	has a positive y-intercept.	

7.	If the regression line is y = 4 – 3x, then the variables	
A)	have a positive association.	
B)	have a negative association.	
C)	have an association that is sometimes positive and sometimes negative.	

8.	If the regression line is 2x + 4y = 10, then the variables	
A)	have a positive association.	
B)	have a negative association.	
C)	have an association that is sometimes positive and sometimes negative.	

9.	If the regression line is x = 5y – 2, then the variables	
A)	have a positive association.	
B)	have a negative association.	
C)	have an association that is sometimes positive and sometimes negative.	

10.	If the variables have a negative association, then their correlation	
A)	must be less than –1.	C)	must be between 0 and 1.	
B)	must be between –1 and 0.	D)	must be greater than 1.	

11.	If the correlation between two variables is 1, then the points of their scatterplot	
A)	all lay within 1 unit of the regression line.	
B)	all lay within  unit of the regression line.	
C)	all lay on the regression line.	
D)	lay so that exactly half of the points are on each side of the regression line.	

12.	If the correlation between two variables is –1, then the points of their scatterplot	
A)	all lay within 1 unit of the regression line.	
B)	all lay within  unit of the regression line.	
C)	all lay on the regression line.	
D)	lay so that exactly half of the points are on each side of the regression line.	

13.	If the points of a scatterplot lie on a straight line, then the correlation	
	A)  must be 1.    B)  must be positive.    C)  must be 0.    D)  must be either 1 or –1.	

14.	If the units of measurement change to larger units, then the correlation	
	A)  becomes larger.    B)  becomes smaller.    C)  does not change.	

15.	How does an outlier effect the correlation?	
A)	A single outlier has no effect.	
B)	A single outlier has minimal effect.	
C)	A single outlier can change the value of the correlation, but not its sign.	
D)	A single outlier can change the value and the sign of the correlation.	

16.	The least-squares regression line minimizes the sum of	
A)	the squares of the shortest distance from each scatterplot point to the regression line.	
B)	the squares of the shortest vertical distance from each scatterplot point to the regression line.	
C)	the squares of the shortest horizontal distance from each scatterplot point to the regression line.	
D)	None of these.	

17.	The slope of the least-squares regression line is	
A)	the correlation between the variables.	
B)	the same sign as the correlation between the variables.	
C)	the opposite of the correlation between the variables.	
D)	the opposite sign of the correlation between the variables.	

18.	The intercept of the least-squares regression line is	
A)	the mean of the y values.	
B)	the mean of the x values.	
C)	the mean of the y values minus the mean of the x values.	
D)	none of these.	

19.	If two variables have a strong positive association, then	
A)	increasing x will cause y to increase.	
B)	making x positive will make y positive.	
C)	doubling x will cause y to double.	
D)	changes in x do not necessarily cause changes in y.	

20.	Standardizing an observational value involves	
A)	subtracting the mean.	
B)	dividing by the mean.	
C)	dividing by the number of samples.	
D)	dividing by one less than the number of samples.	

21.	If the least-squares regression line is y = 3x – 5, then for y = 2, the predicted value for x is	
	A)  1    B)  3    C)      D)  6	

22.	If the least-squares regression line is y = 5x – 3, then for x = 3, the predicted value for y is	
	A)  2    B)  0    C)      D)  12	

23.	For the scatterplot shown below, what can you say about the least-squares regression line?

A)	Its slope is positive.	C)	It stops at y = 800.	
B)	It passes through the point (0,0).	D)	None of these.	

24.	For the scatterplot shown below, what can you say about the correlation?

A)	It is almost 0.	C)	It is exactly 1.	
B)	It is between 0 and 1.	D)	It is greater than 1.	

25.	For the scatterplot shown below, what y value would you expect to be paired with x = 9?

A)	about 500	
B)	about 450	
C)	about 400	
D)	It's not possible to answer this question based on the data.	

26.	For the scatterplot shown below, what can you say about the correlation of the data?

A)	The correlation is nearly –1.	C)	The correlation is nearly 0.	
B)	The correlation is nearly 1.	D)	The data has no correlation.	

27.	For the scatterplot shown below, what can you say about the association of the variables?

A)	The variables are positively correlated.	
B)	The variables are negatively correlated.	
C)	The variables are not correlated.	
D)	The variables are not linearly correlated.	

28.	For the scatterplot shown below, what can you say about outliers in the data set?

A)	There are no apparent outliers.	C)	There are only two outliers.	
B)	There is only one outlier.	D)	There are many outliers.	

29.	For the scatterplot shown below, what can you say about the slope of the least-squares regression line?

A)	The slope is zero.	C)	The slope is negative.	
B)	The slope is positive.	D)	The slope varies.	

30.	For the scatterplot shown below, what conclusions can you reach if you hear 18 chirps a minute?

A)	The temperature is about 87.	
B)	The temperature is about 90.	
C)	This is not a valid answer; 18 is not possible.	
D)	The data of the scatterplot is not valid.	

31.	For the scatterplot below, what can you say about the correlation?

A)	The correlation is greater than 1.	C)	The correlation is between 0 and 1.	
B)	The correlation is exactly 1.	D)	The correlation is negative.	

32.	Suppose the points of a scatterplot lie close to the line 3x + 2y = 6.  The slope of this line is	
	A)  3    B)  2/3    C)  3/2    D)  –3/2	

33.	Suppose the points of a scatterplot lie close to the line y = 3 – 2x.  The slope of this line is	
	A)  3    B)  –2    C)  3/2    D)  –2/3	

34.	Suppose you are taking a survey of young children.  If you measure their height and their weight, what do you expect to determine about this data?	
A)	There is no correlation between the data.	
B)	There is a positive correlation between the data.	
C)	There is a negative correlation between the data.	

35.	For professional baseball players, one would expect a negative correlation between	
A)	batting average and salary.	C)	number of home runs and salary.	
B)	years of play and salary.	D)	number of errors and salary.	

36.	For professional golfer, one would expect a positive correlation between	
A)	average score and number of endorsements.	
B)	age and number of endorsements.	
C)	average score and number of years as a pro.	
D)	none of these.	

37.	A typing service keeps data on the number of pages in a manuscript and the length of time (in hours) it takes to complete the typing.  The least-squares regression line for the data is given by y = 20 + 0.273x.  Use this to predict the length of time needed to type a 40-page manuscript.	
	A)  810.92    B)  60.273    C)  30.92    D)  16.38	

38.	An airline has determined that the relationship between the number of passengers on a flight and the total weight (in pounds) of luggage stored in the baggage compartment can be estimated by the least-squares regression equation y = 250 + 27x.  Predict the weight of luggage for a flight with 125 passengers.	
	A)  402    B)  3625    C)  10,125    D)  34,625	

39.	The least-squares regression equation y = 50 + 0.1x gives the yield in bushels per acre of corn when x pounds of fertilizer are applied.  Predict the yield for a farmer who plans to use 320 pounds of fertilizer.	
	A)  82    B)  16,032    C)  37    D)  50.32	

40.	A bank collects data on the savings and incomes of families to predict an expected increase in certificate of deposit accounts due to a 10% increase in salaries of employees at a local company.  Which variable, savings or income, would be the explanatory variable?	
	A)  Family savings    B)  Family income	

41.	A university admissions counselor wishes to predict the performance of freshmen by considering their SAT scores.  Which variable, freshman GPA or SAT score, would be the explanatory variable in a least-squares regression equation?	
	A)  Freshman GPA    B)  SAT score	

42.	To choose advertising media, a marketing analyst studies the relationship between a consumer's income and the amount of money spent on restaurant dining.  Which variable, consumer's income or dining expenditures, would be the response variable for a least-squares regression equation?	
	A)  Consumers income    B)  Dining expenditures	

43.	To determine the effectiveness of group study sessions, a college instructor gathers data on hours of attendance and exam scores for students in the class.  Which variable, hours of attendance or exam scores, would be the response variable for a least-squares regression equation?	
	A)  Hours of attendance    B)  Exam scores	

44.	Max is collecting baseball cards. He has 65 that his aunt gave him for his birthday, and he buys 20 more each week. The total number y of cards that Max has after x weeks is given by which of the following equations?	
	A)  y = 20 + 65x    B)  y = 65 + 20x    C)  y = 20 + x    D)  y = 85x	

45.	A computer store purchases advertising time on local television stations. For the variables representing the number of advertisements purchased and the number of computers sold, you would expect	
A)	a substantial negative correlation.	C)	a small correlation.	
B)	a substantial positive correlation.	D)	no correlation.	

46.	A shopping mall is having trouble with shoplifting in several of its stores. For the variables representing the number of security guards on patrol and the number of shoplifting incidents, you would expect	
A)	a substantial negative correlation.	C)	a small correlation.	
B)	a substantial positive correlation.	D)	no correlation.	

47.	For the data below, let x = number of chirps per second and y = temperature.  What is the slope of the regression line?

Temperature in degrees F (y)	
70	
72	
74	
75	
81	
82	
83	
84	
89	
93	

Chirps per second	
15	
15	
15	
16	
17	
17	
16	
17	
19	
20	

	A)  about 4    B)  about 11    C)  about 70    D)  None of these.	

48.	For the data below, let x = number of chirps per second and y = temperature.  What is the intercept of the regression line?

Temperature in degrees F	
70	
72	
74	
75	
81	
82	
83	
84	
89	
93	

Chirps per second	
15	
15	
15	
16	
17	
17	
16	
17	
19	
20	

	A)  about 4    B)  about 11    C)  about –11    D)  about 70	

49.	For the data below, what is the correlation between the variables?

Temperature in degrees F	
70	
72	
74	
75	
81	
82	
83	
84	
89	
93	

Chirps per second	
15	
15	
15	
16	
17	
17	
16	
17	
19	
20	

	A)  about 0.99    B)  about 0.94    C)  about 0.70    D)  about 0.50	

50.	For the data below, let x = number of chirps per second and y = temperature.  How many points are above the regression line?

Temperature in degrees F	
70	
72	
74	
75	
81	
82	
83	
84	
89	
93	

Chirps per second	
15	
15	
15	
16	
17	
17	
16	
17	
19	
20	

	A)  4    B)  5    C)  6    D)  None of these.	

51.	For the data below, let x = time spent studying and y = test score.  What is the slope of the regression line?

Time spent 
 studying (hours)	
1	
2	
5	
4	
6	
7	
8	
5	
2	
4	
3	
5	

Test score 
 (percentage)	
49	
57	
80	
70	
88	
91	
98	
80	
57	
72	
65	
82	

	A)  about 2    B)  about 7    C)  about 43    D)  None of these.	

52.	For the data below, let x = time spent studying and y = test score.  What is the intercept of the regression line?

Time spent 
 studying (hours)	
1	
2	
5	
4	
6	
7	
8	
5	
2	
4	
3	
5	

Test score 
 (percentage)	
49	
57	
80	
70	
88	
91	
98	
80	
57	
72	
65	
82	

	A)  about 70    B)  about 48    C)  about 43    D)  None of these.	

53.	For the data below, what is the correlation?

Time spent 
 studying (hours)	
1	
2	
5	
4	
6	
7	
8	
5	
2	
4	
3	
5	

Test score 
 (percentage)	
49	
57	
80	
70	
88	
91	
98	
80	
57	
72	
65	
82	

	A)  about 0.99    B)  about 0.90    C)  about 0.80    D)  about 0.70	

54.	For the data below, what is the expected test score if three hours are spent studying?

Time spent 
 studying (hours)	
1	
2	
5	
4	
6	
7	
8	
5	
2	
4	
3	
5	

Test score 
 (percentage)	
49	
57	
80	
70	
88	
91	
98	
80	
57	
72	
65	
82	

	A)  about 63    B)  about 65    C)  about 67    D)  about 70	

55.	For the data below, each additional hour of studying adds on average how many test points?

Time spent 
 studying (hours)	
1	
2	
5	
4	
6	
7	
8	
5	
2	
4	
3	
5	

Test score 
 (percentage)	
49	
57	
80	
70	
88	
91	
98	
80	
57	
72	
65	
82	

	A)  about 1    B)  about 5    C)  about 7    D)  about 10	

56.	For the data below, if you do not study, on average what test score would you expect?

Time spent 
 studying (hours)	
1	
2	
5	
4	
6	
7	
8	
5	
2	
4	
3	
5	

Test score 
 (percentage)	
49	
57	
80	
70	
88	
91	
98	
80	
57	
72	
65	
82	

	A)  about 43    B)  about 46    C)  about 48    D)  None of these.	

57.	If the x and y coordinates of a scatterplot are exchanged, the slope of the regression line	
A)	remains unchanged.	C)	changes to its negative reciprocal.	
B)	changes to its reciprocal.	D)	none of these.	

58.	If the x and y coordinates of a scatterplot are exchanged, the correlation of the variables	
A)	remains unchanged.	C)	changes to its negative reciprocal.	
B)	changes to its reciprocal.	D)	none of these.	

59.	If the x and y coordinates of a scatterplot are exchanged, intercept of the regression line	
A)	remains unchanged.	C)	changes to its reciprocal.	
B)	changes to its opposite.	D)	none of these.	

60.	If the x and y coordinates of a scatterplot are exchanged, variables that were previously positively associated	
A)	remain positively associated.	C)	are no longer associated.	
B)	are now negatively associated.			

Answer Key

1.	B	
2.	A	
3.	A	
4.	A	
5.	B	
6.	C	
7.	B	
8.	B	
9.	A	
10.	B	
11.	C	
12.	C	
13.	D	
14.	C	
15.	D	
16.	B	
17.	B	
18.	D	
19.	D	
20.	A	
21.	C	
22.	D	
23.	A	
24.	B	
25.	B	
26.	C	
27.	D	
28.	A	
29.	B	
30.	A	
31.	C	
32.	D	
33.	B	
34.	B	
35.	D	
36.	D	
37.	C	
38.	B	
39.	A	
40.	B	
41.	B	
42.	B	
43.	B	
44.	B	
45.	B	
46.	A	
47.	A	
48.	B	
49.	B	
50.	A	
51.	B	
52.	C	
53.	A	
54.	B	
55.	C	
56.	A	
57.	D	
58.	A	
59.	D	
60.	A