SOLUTIONS for
TU
Elementary Statistics Using the TI-
83/84 Plus Calculator, 5th edition
Author (s): Mario F. Triola
VI
A
A
PP
R
O
VE
D
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, Section 1-1: Statistical and Critical Thinking 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
TU
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 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
VI
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 of
any interaction or cause effect relationship between deaths in swimming pools and power generated from
A
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.
A
8. Yes, there does appear to be a potential to create a bias.
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
PP
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.
13. With only a 1% chance of getting such results with a program that has no effect, the program appears to have
R
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.
O
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
significance. The result of 1020 girls in 2000 births (51% girls) is above the approximately 50% rate expected
VE
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
matched.
D
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.
Copyright © 2019 Pearson Education, Inc.
, 2 Chapter 1: Introduction to Statistics
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
TU
are meaningless.
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.
VI
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
A
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 results.
The source is questionable.
29. a. 700 adults
A
b. 55%
30. a. 253.31 subjects
PP
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
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
R
surveyed, the result must be a whole number.
c. 559 respondents
d. 8%
O
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
VE
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 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.
D
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.
35. Because a reduction of 100% would eliminate all plaque, it is not possible to reduce it by more than 100%.
?
Copyright © 2019 Pearson Education, Inc.
, Section 1-2: Types of Data 3
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
TU
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.
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.
VI
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 d. discrete
c. ratio
5. statistic 17. discrete
6. statistic 18. continuous
7. parameter 19. continuous
A
8. parameter 20. discrete
9. statistic 21. ordinal
PP
10. statistic 22. nominal
11. parameter 23. nominal
12. parameter 24. ratio
13. continuous 25. interval
14. continuous 26. ordinal
R
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
O
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 makes
no sense to calculate their average (mean).
VE
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.
D
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.
Copyright © 2019 Pearson Education, Inc.
TU
Elementary Statistics Using the TI-
83/84 Plus Calculator, 5th edition
Author (s): Mario F. Triola
VI
A
A
PP
R
O
VE
D
??
, Section 1-1: Statistical and Critical Thinking 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
TU
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 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
VI
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 of
any interaction or cause effect relationship between deaths in swimming pools and power generated from
A
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.
A
8. Yes, there does appear to be a potential to create a bias.
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
PP
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.
13. With only a 1% chance of getting such results with a program that has no effect, the program appears to have
R
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.
O
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
significance. The result of 1020 girls in 2000 births (51% girls) is above the approximately 50% rate expected
VE
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
matched.
D
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.
Copyright © 2019 Pearson Education, Inc.
, 2 Chapter 1: Introduction to Statistics
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
TU
are meaningless.
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.
VI
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
A
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 results.
The source is questionable.
29. a. 700 adults
A
b. 55%
30. a. 253.31 subjects
PP
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
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
R
surveyed, the result must be a whole number.
c. 559 respondents
d. 8%
O
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
VE
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 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.
D
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.
35. Because a reduction of 100% would eliminate all plaque, it is not possible to reduce it by more than 100%.
?
Copyright © 2019 Pearson Education, Inc.
, Section 1-2: Types of Data 3
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
TU
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.
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.
VI
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 d. discrete
c. ratio
5. statistic 17. discrete
6. statistic 18. continuous
7. parameter 19. continuous
A
8. parameter 20. discrete
9. statistic 21. ordinal
PP
10. statistic 22. nominal
11. parameter 23. nominal
12. parameter 24. ratio
13. continuous 25. interval
14. continuous 26. ordinal
R
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
O
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 makes
no sense to calculate their average (mean).
VE
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.
D
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.
Copyright © 2019 Pearson Education, Inc.
