SOLUTIONS MANUAL
Elementary Statistics, 13th edition
By Mario F. Triola
ST
U
D
YL
A B
, Table of Content
1. Introduction to Statistics
1.1 Statistical and Critical Thinking
1.2 Types of Data
1.3 Collecting Sample Data
1.4 Ethics in Statistics (download only)
2. Exploring Data with Tables and Graphs
2.1 Frequency Distributions for Organizing and Summarizing Data
2.2 Histograms
2.3 Graphs That Enlighten and Graphs That Deceive
2.4 Scatterplots, Correlation, and Regression
3. Describing, Exploring, and Comparing Data
3.1 Measures of Center
ST
3.2 Measures of Variation
3.3 Measures of Relative Standing and Boxplots
4. Probability
4.1 Basic Concepts of Probability
4.2 Addition Rule and Multiplication Rule
4.3 Complements, Conditional Probability, and Bayes' Theorem
U
4.4 Counting
4.5 Simulations for Hypothesis Tests
D
5. Discrete Probability Distributions
5.1 Probability Distributions
5.2 Binomial Probability Distributions
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5.3 Poisson Probability Distributions
6. Normal Probability Distributions
6.1 The Standard Normal Distribution
6.2 Real Applications of Normal Distributions
6.3 Sampling Distributions and Estimators
6.4 The Central Limit Theorem
A
6.5 Assessing Normality
6.6 Normal as Approximation to Binomial (download only)
B
7. Estimating Parameters and Determining Sample Sizes
7.1 Estimating a Population Proportion
7.2 Estimating a Population Mean
7.3 Estimating a Population Standard Deviation or Variance
7.4 Bootstrapping: Using Technology for Estimates
8. Hypothesis Testing
8.1 Basics of Hypothesis Testing
8.2 Testing a Claim About a Proportion
8.3 Testing a Claim About a Mean
8.4 Testing a Claim About a Standard Deviation or Variance
8.5 Resampling: Using Technology for Hypothesis Testing
9. Inferences from Two Samples
9.1 Two Proportions
,9.2 Two Means: Independent Samples
9.3 Matched Pairs
9.4 Two Variances or Standard Deviations
9.5 Resampling: Using Technology for Inferences
10. Correlation and Regression
10.1 Correlation
10.2 Regression
10.3 Prediction Intervals and Variation
10.4 Multiple Regression
10.5 Nonlinear Regression
11. Goodness-of-Fit and Contingency Tables
11.1 Goodness-of-Fit
11.2 Contingency Tables
12. Analysis of Variance
ST
12.1 One-Way ANOVA
12.2 Two-Way ANOVA
13. Nonparametric Tests
13.1 Basics of Nonparametric Tests
13.2 Sign Test
U
13.3 Wilcoxon Signed.Ranks Test for Matched Pairs
13.4 Wilcoxon Rank-Sum Test for Two Independent Samples
13.5 Kruskal-Wallis Test for Three or More Samples
D
13.6 Rank Correlation
13.7 Runs Test for Randomness
14. Statistics Process Control
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14.1 Control Charts for Variation and Mean
14.2 Control Charts for Attributes
A B
, 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
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
ST
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.
U
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.
D
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
YL
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
significance. The result of 1020 girls in 2000 births (51% girls) is above the approximately 50% rate
A
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
B
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.
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.
Elementary Statistics, 13th edition
By Mario F. Triola
ST
U
D
YL
A B
, Table of Content
1. Introduction to Statistics
1.1 Statistical and Critical Thinking
1.2 Types of Data
1.3 Collecting Sample Data
1.4 Ethics in Statistics (download only)
2. Exploring Data with Tables and Graphs
2.1 Frequency Distributions for Organizing and Summarizing Data
2.2 Histograms
2.3 Graphs That Enlighten and Graphs That Deceive
2.4 Scatterplots, Correlation, and Regression
3. Describing, Exploring, and Comparing Data
3.1 Measures of Center
ST
3.2 Measures of Variation
3.3 Measures of Relative Standing and Boxplots
4. Probability
4.1 Basic Concepts of Probability
4.2 Addition Rule and Multiplication Rule
4.3 Complements, Conditional Probability, and Bayes' Theorem
U
4.4 Counting
4.5 Simulations for Hypothesis Tests
D
5. Discrete Probability Distributions
5.1 Probability Distributions
5.2 Binomial Probability Distributions
YL
5.3 Poisson Probability Distributions
6. Normal Probability Distributions
6.1 The Standard Normal Distribution
6.2 Real Applications of Normal Distributions
6.3 Sampling Distributions and Estimators
6.4 The Central Limit Theorem
A
6.5 Assessing Normality
6.6 Normal as Approximation to Binomial (download only)
B
7. Estimating Parameters and Determining Sample Sizes
7.1 Estimating a Population Proportion
7.2 Estimating a Population Mean
7.3 Estimating a Population Standard Deviation or Variance
7.4 Bootstrapping: Using Technology for Estimates
8. Hypothesis Testing
8.1 Basics of Hypothesis Testing
8.2 Testing a Claim About a Proportion
8.3 Testing a Claim About a Mean
8.4 Testing a Claim About a Standard Deviation or Variance
8.5 Resampling: Using Technology for Hypothesis Testing
9. Inferences from Two Samples
9.1 Two Proportions
,9.2 Two Means: Independent Samples
9.3 Matched Pairs
9.4 Two Variances or Standard Deviations
9.5 Resampling: Using Technology for Inferences
10. Correlation and Regression
10.1 Correlation
10.2 Regression
10.3 Prediction Intervals and Variation
10.4 Multiple Regression
10.5 Nonlinear Regression
11. Goodness-of-Fit and Contingency Tables
11.1 Goodness-of-Fit
11.2 Contingency Tables
12. Analysis of Variance
ST
12.1 One-Way ANOVA
12.2 Two-Way ANOVA
13. Nonparametric Tests
13.1 Basics of Nonparametric Tests
13.2 Sign Test
U
13.3 Wilcoxon Signed.Ranks Test for Matched Pairs
13.4 Wilcoxon Rank-Sum Test for Two Independent Samples
13.5 Kruskal-Wallis Test for Three or More Samples
D
13.6 Rank Correlation
13.7 Runs Test for Randomness
14. Statistics Process Control
YL
14.1 Control Charts for Variation and Mean
14.2 Control Charts for Attributes
A B
, 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
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
ST
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.
U
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.
D
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
YL
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
significance. The result of 1020 girls in 2000 births (51% girls) is above the approximately 50% rate
A
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
B
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.
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.
