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11. Which one of these statistics is unaffected by outliers?

a. Mean

b. Interquartile range

c. Standard deviation

d. Range

12. A list of 5 pulse rates is: 70, 64, 80, 74, 92. What is the median for this list?

a. 74 b. 76 c. 77 d. 80

13. Which of the following would indicate that a dataset is not bell-shaped?

a. The range is equal to 5 standard deviations.

b. The range is larger than the interquartile range.

c. The mean is much smaller than the median.

d. There are no outliers.

14. A scatter plot of number of teachers and number of people with college degrees for cities in

California reveals a positive association. The most likely explanation for this positive

association is:

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. 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.

c. 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.

d. 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.

15. The value of a correlation is reported by a researcher to be r = 0.5. Which of the following

statements is correct?

a. The x-variable explains 25% of the variability in the y-variable.

b. The x-variable explains 25% of the variability in the y-variable.

c. The x-variable explains 50% of the variability in the y-variable.

d. The x-variable explains 50% of the variability in the y-variable.

16. What is the effect of an outlier on the value of 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.

17. One use of a regression line is

a. to determine if any x-values are outliers.

b. to determine if any y-values are outliers.

c. to determine if a change in x causes a change in y.

d. to estimate the change in y for a one-unit change in x.

18. Past data has shown that the regression line relating the final exam score and the midterm

exam score for students who take statistics from a certain professor is:

final exam = 50 + 0.5 midterm

One interpretation of the slope is

a. a student who scored 0 on the midterm would be predicted to score 50 on the final exam.

b. a student who scored 0 on the final exam would be predicted to score 50 on the midterm

exam.

c. a student who scored 10 points higher than another student on the midterm would be

predicted to score 5 points higher than the other student on the final exam.

d. students only receive half as much credit (.5) for a correct answer on the final exam

compared to a correct answer on the midterm exam.

Questions 19 to 21: A survey asked people how often they exceed speed limits. The data are

then categorized into the following contingency table of counts showing the relationship between

age group and response.

Exceed Limit if Possible?

Age Always Not Always Total

Under 30 100 100 200

Over 30 40 160 200

Total 140 260 400

19. Among people with age over 30, what's the "risk" of always exceeding the speed limit?

a. 0.20

b. 0.40

c. 0.33

d. 0.50

20. Among people with age under 30 what are the odds that they always exceed the speed limit?

a. 1 to 2

b. 2 to 1

c. 1 to 1

d. 50%