INSTRUCTOR’S
SOLUTIONS MANUAL
@A
JAMES LAPP
Colorado Mesa University
pl
ELEMENTARY STATISTICS
us
THIRTEENTH EDITION
Mario F. Triola
st
uv
ia
@Aplusstuvia
, Chapter 1: Introduction to Statistics 1
Chapter 1: Introduction to Statistics
Section 1-1: Statistical and Critical Thinking
1. The respondents are a voluntary response sample or a self-selected sample. Because those with strong
interests in the topic are more likely to respond, it is very possible that their responses do not reflect the
opinions or behavior of the general population.
2. a. The sample consists of the 1046 adults who were surveyed. The population consists of all adults.
b. When asked, respondents might be inclined to avoid the shame of the unhealthy habit of not washing
@A
their hands, so the reported rate of 70% might well be much higher than it is in reality. It is generally
better to observe or measure human behavior than to ask subjects about it.
3. Statistical significance is indicated when methods of statistics are used to reach a conclusion that a
treatment is effective, but common sense might suggest that the treatment does not make enough of a
difference to justify its use or to be practical. Yes, it is possible for a study to have statistical significance,
but not practical significance.
4. No. Correlation does not imply causation. The example illustrates a correlation that is clearly not the result
pl
of any interaction or cause effect relationship between deaths in swimming pools and power generated from
nuclear power plants.
5. Yes, there does appear to be a potential to create a bias.
6. No, there does not appear to be a potential to create a bias.
7. No, there does not appear to be a potential to create a bias.
8. Yes, there does appear to be a potential to create a bias.
us
9. The sample is a voluntary response sample and has strong potential to be flawed.
10. The samples are voluntary response samples and have potential for being flawed, but this approach might
be necessary due to ethical considerations involved in randomly selecting subjects and somehow imposing
treatments on them.
11. The sampling method appears to be sound.
12. The sampling method appears to be sound.
st
13. With only a 1% chance of getting such results with a program that has no effect, the program appears to
have statistical significance. Also, because the average loss of 22 pounds does seem substantial, the
program appears to also have practical significance.
14. Because there is a 0.3% chance of getting such results by chance, the increase in scores does appear to have
statistical significance. The typical increase of 5 points suggests that the course does have practical
significance. The course does appear to be successful.
15. Because there is a 19% chance of getting that many girls by chance, the method appears to lack statistical
uv
significance. The result of 1020 girls in 2000 births (51% girls) is above the approximately 50% rate
expected by chance, but it does not appear to be high enough to have practical significance. Not many
couples would bother with a procedure that raises the likelihood of a girl from 50% to 51%.
16. Because there is a 25% chance of getting such results with a program that has no effect, the program does
not appear to have statistical significance. Because the average increase is only 3 IQ points, the program
does not appear to have practical significance.
17. Yes. Each column of 8 AM and 12 AM temperatures is recorded from the same subject, so each pair is
ia
matched.
18. No. The source is from university researchers who do not appear to gain from distorting the data.
19. The data can be used to address the issue of whether there is a correlation between body temperatures at
8 AM and at 12 AM. Also, the data can be used to determine whether there are differences between body
temperatures at 8 AM and at 12 AM.
20. Because the differences could easily occur by chance (with a 64% chance), the differences do not appear to
have statistical significance.
21. No. The white blood cell counts measure a different quantity than the red blood cell counts, so their
differences are meaningless.
Copyright © 2018 Pearson Education, Inc.
@Aplusstuvia
, 2 Elementary Statistics, 13th edition
22. The issue that can be addressed is whether there is a correlation, or association, between white blood cell
counts and red blood cell counts.
23. No. The National Center for Health Statistics has no reason to collect or present the data in a way that is
biased.
24. No. Correlation does not imply causation, so a statistical correlation between white blood cell counts and
red blood cell counts should not be used to conclude that higher white blood cell counts are the cause of
higher red blood cell counts.
@A
25. It is questionable that the sponsor is the Idaho Potato Commission and the favorite vegetable is potatoes.
26. The sample is a voluntary response sample, so there is a good chance that the results do not reflect the
larger population of people who have a water preference.
27. The correlation, or association, between two variables does not mean that one of the variables is the cause
of the other. Correlation does not imply causation. Clearly, sour cream consumption is not directly related
in any way to motorcycle fatalities.
28. The sponsor of the poll is an electronic cigarette maker, so the sponsor does have an interest in the poll
pl
results. The source is questionable.
29. a. 700 adults
b. 55%
30. a. 253.31 subjects
b. No. Because the result is a count of people among the 347 who were surveyed, the result must be a
whole number.
c. 253 subjects
us
d. 32%
31. a. 559.2 respondents
b. No. Because the result is a count of respondents among the 1165 engaged or married women who were
surveyed, the result must be a whole number.
c. 559 respondents
d. 8%
st
32. a. 293.17 women
b. No. Because the result is a count of women among the 1543 who were surveyed, the result must be a
whole number.
c. 293 women
d. 15%
e. Interpretations of a “typical” week and what it means to “kick back and relax” might vary considerably
by different survey respondents. The survey might be improved by asking about behavior within “the
uv
past seven days” instead of a “typical” week. Instead of “kick back and relax,” respondents might be
surveyed about specific behavior, such as reading, taking a nap, watching television, listening to music,
or going for a walk.
33. Because a reduction of 100% would eliminate all of the size, it is not possible to reduce the size by 100%
or more.
34. In an editorial criticizing the statement, the New York Times correctly interpreted the 100% improvement to
mean that no baggage is being lost, which was not true.
ia
35. Because a reduction of 100% would eliminate all plaque, it is not possible to reduce it by more than 100%.
36. If one subgroup receives a 4% raise and another subgroup receives a 4% raise, the combined group will
receive a 4% raise, not an 8% raise. The percentages should not be added in this case.
37. The wording of the question is biased and tends to encourage negative responses. The sample size of 20 is
too small. Survey respondents are self-selected instead of being randomly selected by the newspaper. If 20
readers respond, the percentages should be multiples of 5, so 87% and 13% are not possible results.
38. All percentages of success should be multiples of 5. The given percentages cannot be correct.
Copyright © 2018 Pearson Education, Inc.
@Aplusstuvia
, Chapter 1: Introduction to Statistics 3
Section 1-2: Types of Data
1. The population consists of all adults in the United States, and the sample is the 2276 adults who were
surveyed. Because the value of 33% refers to the sample, it is a statistic.
2. a. quantitative c. categorical
b. categorical d. quantitative
3. Only part (a) describes discrete data.
4. a. The sample is the 1020 adults who were surveyed. The population is all adults in the United States.
@A
b. statistic
c. ratio
d. discrete
5. statistic 17. discrete
6. statistic 18. continuous
7. parameter 19. continuous
pl
8. parameter 20. discrete
9. statistic 21. ordinal
10. statistic 22. nominal
11. parameter 23. nominal
12. parameter 24. ratio
13. continuous 25. interval
us
14. continuous 26. ordinal
15. discrete 27. ordinal
16. discrete 28. interval
29. The numbers are not counts or measures of anything. They are at the nominal level of measurement, and it
makes no sense to compute the average (mean) of them.
30. The digits are not counts or measures of anything. They are at the nominal level of measurement and it
st
makes no sense to calculate their average (mean).
31. The temperatures are at the interval level of measurement. Because there is no natural starting point with
0 F representing “no heat,” ratios such as “twice” make no sense, so it is wrong to say that it is twice as
warm at the author’s home as it is in Auckland, New Zealand.
32. The ranks are at the ordinal level of measurement. Differences between the universities cannot be
determined, so there is no way to know whether the difference between Princeton and Harvard is the same
as the difference between Yale and Columbia.
uv
33. a. Continuous, because the number of possible values is infinite and not countable.
b. Discrete, because the number of possible values is finite.
c. Discrete, because the number of possible values is finite.
d. Discrete, because the number of possible values is infinite and countable.
Section 1-3: Collecting Sample Data
1. The study is an experiment because subjects were given treatments.
ia
2. The subjects in the study did not know whether they were taking a placebo or the paracetamol medication,
and those who administered the pills also did not know.
3. The group sample sizes of 547, 550, and 546 are all large so that the researchers could see the effects of the
paracetamol treatment.
4. The sample appears to be a convenience sample. Given that the subjects were randomly assigned to the
three different treatment groups, it appears that the results of the study are good because they are not likely
to be distorted from bias, but we should investigate the sample groups to ensure that they are not
fundamentally different from the population.
Copyright © 2018 Pearson Education, Inc.
@Aplusstuvia
SOLUTIONS MANUAL
@A
JAMES LAPP
Colorado Mesa University
pl
ELEMENTARY STATISTICS
us
THIRTEENTH EDITION
Mario F. Triola
st
uv
ia
@Aplusstuvia
, Chapter 1: Introduction to Statistics 1
Chapter 1: Introduction to Statistics
Section 1-1: Statistical and Critical Thinking
1. The respondents are a voluntary response sample or a self-selected sample. Because those with strong
interests in the topic are more likely to respond, it is very possible that their responses do not reflect the
opinions or behavior of the general population.
2. a. The sample consists of the 1046 adults who were surveyed. The population consists of all adults.
b. When asked, respondents might be inclined to avoid the shame of the unhealthy habit of not washing
@A
their hands, so the reported rate of 70% might well be much higher than it is in reality. It is generally
better to observe or measure human behavior than to ask subjects about it.
3. Statistical significance is indicated when methods of statistics are used to reach a conclusion that a
treatment is effective, but common sense might suggest that the treatment does not make enough of a
difference to justify its use or to be practical. Yes, it is possible for a study to have statistical significance,
but not practical significance.
4. No. Correlation does not imply causation. The example illustrates a correlation that is clearly not the result
pl
of any interaction or cause effect relationship between deaths in swimming pools and power generated from
nuclear power plants.
5. Yes, there does appear to be a potential to create a bias.
6. No, there does not appear to be a potential to create a bias.
7. No, there does not appear to be a potential to create a bias.
8. Yes, there does appear to be a potential to create a bias.
us
9. The sample is a voluntary response sample and has strong potential to be flawed.
10. The samples are voluntary response samples and have potential for being flawed, but this approach might
be necessary due to ethical considerations involved in randomly selecting subjects and somehow imposing
treatments on them.
11. The sampling method appears to be sound.
12. The sampling method appears to be sound.
st
13. With only a 1% chance of getting such results with a program that has no effect, the program appears to
have statistical significance. Also, because the average loss of 22 pounds does seem substantial, the
program appears to also have practical significance.
14. Because there is a 0.3% chance of getting such results by chance, the increase in scores does appear to have
statistical significance. The typical increase of 5 points suggests that the course does have practical
significance. The course does appear to be successful.
15. Because there is a 19% chance of getting that many girls by chance, the method appears to lack statistical
uv
significance. The result of 1020 girls in 2000 births (51% girls) is above the approximately 50% rate
expected by chance, but it does not appear to be high enough to have practical significance. Not many
couples would bother with a procedure that raises the likelihood of a girl from 50% to 51%.
16. Because there is a 25% chance of getting such results with a program that has no effect, the program does
not appear to have statistical significance. Because the average increase is only 3 IQ points, the program
does not appear to have practical significance.
17. Yes. Each column of 8 AM and 12 AM temperatures is recorded from the same subject, so each pair is
ia
matched.
18. No. The source is from university researchers who do not appear to gain from distorting the data.
19. The data can be used to address the issue of whether there is a correlation between body temperatures at
8 AM and at 12 AM. Also, the data can be used to determine whether there are differences between body
temperatures at 8 AM and at 12 AM.
20. Because the differences could easily occur by chance (with a 64% chance), the differences do not appear to
have statistical significance.
21. No. The white blood cell counts measure a different quantity than the red blood cell counts, so their
differences are meaningless.
Copyright © 2018 Pearson Education, Inc.
@Aplusstuvia
, 2 Elementary Statistics, 13th edition
22. The issue that can be addressed is whether there is a correlation, or association, between white blood cell
counts and red blood cell counts.
23. No. The National Center for Health Statistics has no reason to collect or present the data in a way that is
biased.
24. No. Correlation does not imply causation, so a statistical correlation between white blood cell counts and
red blood cell counts should not be used to conclude that higher white blood cell counts are the cause of
higher red blood cell counts.
@A
25. It is questionable that the sponsor is the Idaho Potato Commission and the favorite vegetable is potatoes.
26. The sample is a voluntary response sample, so there is a good chance that the results do not reflect the
larger population of people who have a water preference.
27. The correlation, or association, between two variables does not mean that one of the variables is the cause
of the other. Correlation does not imply causation. Clearly, sour cream consumption is not directly related
in any way to motorcycle fatalities.
28. The sponsor of the poll is an electronic cigarette maker, so the sponsor does have an interest in the poll
pl
results. The source is questionable.
29. a. 700 adults
b. 55%
30. a. 253.31 subjects
b. No. Because the result is a count of people among the 347 who were surveyed, the result must be a
whole number.
c. 253 subjects
us
d. 32%
31. a. 559.2 respondents
b. No. Because the result is a count of respondents among the 1165 engaged or married women who were
surveyed, the result must be a whole number.
c. 559 respondents
d. 8%
st
32. a. 293.17 women
b. No. Because the result is a count of women among the 1543 who were surveyed, the result must be a
whole number.
c. 293 women
d. 15%
e. Interpretations of a “typical” week and what it means to “kick back and relax” might vary considerably
by different survey respondents. The survey might be improved by asking about behavior within “the
uv
past seven days” instead of a “typical” week. Instead of “kick back and relax,” respondents might be
surveyed about specific behavior, such as reading, taking a nap, watching television, listening to music,
or going for a walk.
33. Because a reduction of 100% would eliminate all of the size, it is not possible to reduce the size by 100%
or more.
34. In an editorial criticizing the statement, the New York Times correctly interpreted the 100% improvement to
mean that no baggage is being lost, which was not true.
ia
35. Because a reduction of 100% would eliminate all plaque, it is not possible to reduce it by more than 100%.
36. If one subgroup receives a 4% raise and another subgroup receives a 4% raise, the combined group will
receive a 4% raise, not an 8% raise. The percentages should not be added in this case.
37. The wording of the question is biased and tends to encourage negative responses. The sample size of 20 is
too small. Survey respondents are self-selected instead of being randomly selected by the newspaper. If 20
readers respond, the percentages should be multiples of 5, so 87% and 13% are not possible results.
38. All percentages of success should be multiples of 5. The given percentages cannot be correct.
Copyright © 2018 Pearson Education, Inc.
@Aplusstuvia
, Chapter 1: Introduction to Statistics 3
Section 1-2: Types of Data
1. The population consists of all adults in the United States, and the sample is the 2276 adults who were
surveyed. Because the value of 33% refers to the sample, it is a statistic.
2. a. quantitative c. categorical
b. categorical d. quantitative
3. Only part (a) describes discrete data.
4. a. The sample is the 1020 adults who were surveyed. The population is all adults in the United States.
@A
b. statistic
c. ratio
d. discrete
5. statistic 17. discrete
6. statistic 18. continuous
7. parameter 19. continuous
pl
8. parameter 20. discrete
9. statistic 21. ordinal
10. statistic 22. nominal
11. parameter 23. nominal
12. parameter 24. ratio
13. continuous 25. interval
us
14. continuous 26. ordinal
15. discrete 27. ordinal
16. discrete 28. interval
29. The numbers are not counts or measures of anything. They are at the nominal level of measurement, and it
makes no sense to compute the average (mean) of them.
30. The digits are not counts or measures of anything. They are at the nominal level of measurement and it
st
makes no sense to calculate their average (mean).
31. The temperatures are at the interval level of measurement. Because there is no natural starting point with
0 F representing “no heat,” ratios such as “twice” make no sense, so it is wrong to say that it is twice as
warm at the author’s home as it is in Auckland, New Zealand.
32. The ranks are at the ordinal level of measurement. Differences between the universities cannot be
determined, so there is no way to know whether the difference between Princeton and Harvard is the same
as the difference between Yale and Columbia.
uv
33. a. Continuous, because the number of possible values is infinite and not countable.
b. Discrete, because the number of possible values is finite.
c. Discrete, because the number of possible values is finite.
d. Discrete, because the number of possible values is infinite and countable.
Section 1-3: Collecting Sample Data
1. The study is an experiment because subjects were given treatments.
ia
2. The subjects in the study did not know whether they were taking a placebo or the paracetamol medication,
and those who administered the pills also did not know.
3. The group sample sizes of 547, 550, and 546 are all large so that the researchers could see the effects of the
paracetamol treatment.
4. The sample appears to be a convenience sample. Given that the subjects were randomly assigned to the
three different treatment groups, it appears that the results of the study are good because they are not likely
to be distorted from bias, but we should investigate the sample groups to ensure that they are not
fundamentally different from the population.
Copyright © 2018 Pearson Education, Inc.
@Aplusstuvia
