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Elementary Statistics Using Excel – 7th Edition by Triola | Complete Solutions Manual

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This solutions manual for the 7th Edition of Elementary Statistics Using Excel by Mario F. Triola provides detailed solutions to all textbook exercises. It covers key statistical topics including descriptive statistics, probability distributions, hypothesis testing, confidence intervals, regression, and Excel-based statistical analysis. Ideal for students in statistics courses using Microsoft Excel as a tool for data analysis and interpretation.

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Institution
Elementary Statistics Using Excel, 7th Edition
Course
Elementary Statistics Using Excel, 7th edition











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Institution
Elementary Statistics Using Excel, 7th edition
Course
Elementary Statistics Using Excel, 7th edition

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Uploaded on
June 13, 2025
Number of pages
585
Written in
2024/2025
Type
Exam (elaborations)
Contains
Questions & answers

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SOLUTIONS for
Elementary Statistics Using Excel,
7th edition
Author (s): Mario F. Triola
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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
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
effective, but common sense might suggest that the treatment does not make enough of a difference to justify its
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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 per capita consumption of margarine and the divorce rate in
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Maine.
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.
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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.
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12. The sampling method appears to be sound.
13. The Ornish weight loss program has statistical significance, because the results are so unlikely (3 chances in
1000) to occur by chance. It does not have practical significance because the amount of lost weight (3.3 lb) is so
small.
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14. Because there is only one chance in a thousand of getting such success rates by chance, the difference does
appear to have statistical significance. The 92% success rate for surgery appears to be substantially better than
the 72% success rate for splints, so the difference does appear to have practical significance.
15. The difference between Mendel’s 25% rate and the result of 26% is not statistically significant. According to
Mendel’s theory, 145 of the 580 peas would have yellow pods, but the results consisted of 152 peas with yellow
pods. The difference of 7 peas with yellow pods among the 580 offspring does not appear to be statistically
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significant. The difference does not appear to have practical significance.
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.
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17. With 40 out of 41 ballots having the Democrat first, it appears that the result is statistically significant. Because
of the great advantage enjoyed by Democrats, the results also have practical significance.
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18. Because it is so unlikely (0.3%) to get these results by chance, the results have statistical significance. With
about 57% (from 235/414) of the coin toss winners going on to win the game, the result appears to have
practical significance.
19. There appears to be statistical significance given the large discrepancy between 79.1% and 39%. Because the
results are so far from yielding a jury of peers, it appears that the results have practical significance.
20. With only a 0.0000006% chance of getting such results, it appears that the results are statistically significant.
The discrepancy between the 61% rate for voters who actually did vote and the 70% rate of those who said that
they voted is a fairly large discrepancy, and the results appear to have practical significance.



Copyright © 2022 Pearson Education, Inc.

,2 Chapter 1: Introduction to Statistics

21. Yes. Each column of 8 AM and 12 AM temperatures is recorded from the same subject, so each pair is
matched.
22. No. The source is from university researchers who do not appear to gain from distorting the data.
23. 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.
24. Because the differences could easily occur by chance (with a 64% chance), the differences do not appear to
have statistical significance.
25. No. The lemon imports are weights in metric tons and the crash fatality rates are fatalities per 100,000
population, so their differences are meaningless.
26. The issue that can be addressed is whether there is a correlation, or association, between lemon imports and
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crash fatality rates.
27. No. The author of an article for the Journal of Chemical Information and Modeling has no reason to collect or
present the data in a way that is biased.
28. No. Correlation does not imply causation, so a statistical correlation between lemon imports and crash fatality
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rates should not be used to conclude that lemon imports are the cause of fatal crashes.
29. It is questionable that the sponsor is the Idaho Potato Commission and the favorite vegetable is potatoes.
30. 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.
31. The correlation, or association, between two variables does not mean that one of the variables is the cause of the
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other. Correlation does not imply causation. Clearly, sour cream consumption is not directly related in any way
to motorcycle fatalities.
32. 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.
33. The correlation, or association, between two variables does not mean that one of the variables is the cause of the
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other. Correlation does not imply causation.
34. 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.
35. The sample is a voluntary response sample, so there is a good chance that the results do not accurately reflect
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the larger population.
36. Because the nutritionists are paid such large amounts of money, they might be more inclined to find favorable
results. It is very possible that the results represent desired outcomes instead of actual outcomes.
37. a. 700 adults
b. 55%
38. a. 253.31 subjects
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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%
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39. a. 559.2 respondents
b. No. Because the result is a count of respondents among the 1165 engaged or married women who were
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surveyed, the result must be a whole number.
c. 559 respondents
d. 8%
40. a. 847.56 drivers
b. No. Because the result is a count of respondents saying that they text while driving, the result must be a
whole number.
c. 848 drivers
d. Given that texting while driving is extremely dangerous, the result of 42% of drivers who text while driving
is far too high. The result suggests that steps should be taken to substantially lower that rate.


Copyright © 2022 Pearson Education, Inc.

, Section 1-2: Types of Data 3

41. Because a reduction of 100% would eliminate all of the size, it is not possible to reduce the size by 100% or
more.
42. 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.
43. Because a reduction of 100% would eliminate all plaque, it is not possible to reduce it by more than 100%.
44. Because a reduction of 100% would eliminate all car thefts, it is not possible to reduce it by more than 100%.
45. 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.
46. 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.
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47. 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 1001 adults who were surveyed.
Because the value of 69% refers to the sample, it is a statistic.
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2. a. quantitative c. categorical
b. categorical d. quantitative
3. Only part (b) describes discrete data.
4. a. The sample is the 36,000 adults who were surveyed. The population is all adults in the United States.
b. statistic
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c. ratio
d. discrete
5. statistic 17. continuous
6. parameter 18. discrete
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7. parameter 19. discrete
8. statistic 20. continuous
9. statistic 21. nominal
10. statistic 22. ordinal
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11. parameter 23. ordinal
12. parameter 24. ratio
13. continuous 25. interval
14. continuous 26. nominal
15. discrete 27. ratio
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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 makes
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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
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representing “no heat,” ratios such as “twice” make no sense, so it is wrong to say that it is twice as warm in
Paris as it is in Anchorage.
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 Harvard and MIT is the same as the difference
between Stanford and the University of California at Berkeley.
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 © 2022 Pearson Education, Inc.

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