SOLUTIONS MANUAL
** All Chapters included
,Table of Contents are given below
1. Stats Starts Here
2. Displaying and Describing Categorical Data
3. Displaying and Summarizing Quantitative Data
4. Understanding and Comparing Distributions
5. The Standard Deviation as a Ruler and the Normal Model
6. Sample Surveys
7. Experiments and Observational Studies
8. Designing a Statistical Study
9. From Randomness to Probability
10. Probability Rules!
11. Probability Models
12. Sampling Distribution Models
13. Confidence Intervals for Proportions
14. Testing Hypotheses About Proportions
15. More About Tests and Intervals
16. Comparing Two Proportions
17. Associations Between Categorical Variables
18. Inferences About Means
19. Comparing Means
20. Paired Samples and Blocks
21. Scatterplots, Association, and Correlation
22. Linear Regression
23. Inferences for Regression
, Chapter 1 Stats Starts Here 1
Chapter 1 – Stats Starts Here
1. Grocery shopping. This is a good investigative question because it can be answered
with data. The grocery store chain could compare shopping habits of customers
before and after offering the exclusive discounts. Possible data to collect could be
number of items purchased per trip, average amount spent per trip, or number of
visits to the store per week. All of this data could help paint a picture of the
shoppers’ spending habits.
2. Internal combustion engines. This is not a good investigative question because it
cannot be answered with data. To answer this question, a learner must research the
mechanics of how an engine works. No data collection is required.
3. Online shopping. This is not a good investigative question because it cannot be
answered with data. A question about what’s going to happen in the future is
interesting, but we cannot answer it by collecting and analyzing data.
4. Satellites and global climate change. This is a good investigative question because
we can use data to answer it. The data collected by satellites could be used to find
patterns in the rise and fall of temperature, water levels, air quality, and other
atmospheric changes. Looking at these measurements over time could help
researchers find trends in how the climate has changed.
5. Super Bowl. When collecting data about the Super Bowl, the games themselves are
the Who.
6. Nobel laureates. Each year is a case, holding all of the information about that
specific year. Therefore, the year is the Who.
7. Health records. The sample is about 5,000 people, and the population is all
residents of the United States of America. The Who is the selected subjects and the
What includes medical, dental, and physiological measurements and laboratory test
results.
8. Facebook. The Who is the 350 million photos. The What might be information about
the photos, for example: file format, file size, time and date when uploaded, people
and places tagged, and GPS information.
9. Stock market predictions. The response is a categorical variable.
10. Stock market predictions by party. The responses are two categorical variables
(political party and stock market prediction).
, 2 Part I Exploring and Understanding Data
11. Medicine. The company is measuring minutes, a quantitative variable.
12. Stress. The researcher is measuring heart rate, a quantitative variable.
13. The news. Answers will vary.
14. Popular media. Answers will vary.
15. Bicycle and pedestrian safety. Who – pedestrians and bicyclists killed or severely
injured in New York City between 2010 and 2014. What – proportion of pedestrians
and bicyclists killed or injured by left-turning and right-turning vehicles. Population
of interest – Answers may vary. Perhaps: All pedestrians and bicyclists killed or
severely injured in New York City between 2010 and 2014 or all pedestrians and
bicyclists killed or severely injured in New York City in any year or all pedestrians
and bicyclists killed or severely injured in major U.S. cities. Discuss with students
why these and other solutions may be problematic.
16. Investments. Who – 30 companies with similar retirement plans. What – 401(k)
employee participation rates. Population of interest – All companies with similar
retirement plans.
17. Fake news. Who – Middle school, high school, and college students in 12 states.
What – Ability to evaluate the quality of information found in different online
resources. Population of interest – All U.S middle school, high school, and college
students.
18. Not-so-diet soda. Who – 474 participants. What – whether or not the participant
drank two or more diet sodas per day, waist size at the beginning of the study, and
waist size at the end of the study. Population of interest – All people.
19. Blindness. Who – 24 patients. What – Whether or not stem cell therapy was effective
in treating Stargardt’s disease and/or dry age-related macular degeneration.
Population of interest – All people with these eye conditions.
20. Molten iron. Who – 10 castings at Cleveland Casting. What – The pouring
temperature (in degrees Fahrenheit) of molten iron. Population of interest – All
castings at Cleveland Casting.
21. Weighing bears. Who – 54 bears. What – Weight, neck size, length (no specified
units), and sex. When – Not specified. Where – Not specified. Why - Since bears are
difficult to weigh, the researchers hope to use the relationships between weight,
neck size, length, and sex of bears to estimate the weight of bears, given the other,
more observable features of the bear.
How – Researchers collected data on 54 bears they were able to catch.
** All Chapters included
,Table of Contents are given below
1. Stats Starts Here
2. Displaying and Describing Categorical Data
3. Displaying and Summarizing Quantitative Data
4. Understanding and Comparing Distributions
5. The Standard Deviation as a Ruler and the Normal Model
6. Sample Surveys
7. Experiments and Observational Studies
8. Designing a Statistical Study
9. From Randomness to Probability
10. Probability Rules!
11. Probability Models
12. Sampling Distribution Models
13. Confidence Intervals for Proportions
14. Testing Hypotheses About Proportions
15. More About Tests and Intervals
16. Comparing Two Proportions
17. Associations Between Categorical Variables
18. Inferences About Means
19. Comparing Means
20. Paired Samples and Blocks
21. Scatterplots, Association, and Correlation
22. Linear Regression
23. Inferences for Regression
, Chapter 1 Stats Starts Here 1
Chapter 1 – Stats Starts Here
1. Grocery shopping. This is a good investigative question because it can be answered
with data. The grocery store chain could compare shopping habits of customers
before and after offering the exclusive discounts. Possible data to collect could be
number of items purchased per trip, average amount spent per trip, or number of
visits to the store per week. All of this data could help paint a picture of the
shoppers’ spending habits.
2. Internal combustion engines. This is not a good investigative question because it
cannot be answered with data. To answer this question, a learner must research the
mechanics of how an engine works. No data collection is required.
3. Online shopping. This is not a good investigative question because it cannot be
answered with data. A question about what’s going to happen in the future is
interesting, but we cannot answer it by collecting and analyzing data.
4. Satellites and global climate change. This is a good investigative question because
we can use data to answer it. The data collected by satellites could be used to find
patterns in the rise and fall of temperature, water levels, air quality, and other
atmospheric changes. Looking at these measurements over time could help
researchers find trends in how the climate has changed.
5. Super Bowl. When collecting data about the Super Bowl, the games themselves are
the Who.
6. Nobel laureates. Each year is a case, holding all of the information about that
specific year. Therefore, the year is the Who.
7. Health records. The sample is about 5,000 people, and the population is all
residents of the United States of America. The Who is the selected subjects and the
What includes medical, dental, and physiological measurements and laboratory test
results.
8. Facebook. The Who is the 350 million photos. The What might be information about
the photos, for example: file format, file size, time and date when uploaded, people
and places tagged, and GPS information.
9. Stock market predictions. The response is a categorical variable.
10. Stock market predictions by party. The responses are two categorical variables
(political party and stock market prediction).
, 2 Part I Exploring and Understanding Data
11. Medicine. The company is measuring minutes, a quantitative variable.
12. Stress. The researcher is measuring heart rate, a quantitative variable.
13. The news. Answers will vary.
14. Popular media. Answers will vary.
15. Bicycle and pedestrian safety. Who – pedestrians and bicyclists killed or severely
injured in New York City between 2010 and 2014. What – proportion of pedestrians
and bicyclists killed or injured by left-turning and right-turning vehicles. Population
of interest – Answers may vary. Perhaps: All pedestrians and bicyclists killed or
severely injured in New York City between 2010 and 2014 or all pedestrians and
bicyclists killed or severely injured in New York City in any year or all pedestrians
and bicyclists killed or severely injured in major U.S. cities. Discuss with students
why these and other solutions may be problematic.
16. Investments. Who – 30 companies with similar retirement plans. What – 401(k)
employee participation rates. Population of interest – All companies with similar
retirement plans.
17. Fake news. Who – Middle school, high school, and college students in 12 states.
What – Ability to evaluate the quality of information found in different online
resources. Population of interest – All U.S middle school, high school, and college
students.
18. Not-so-diet soda. Who – 474 participants. What – whether or not the participant
drank two or more diet sodas per day, waist size at the beginning of the study, and
waist size at the end of the study. Population of interest – All people.
19. Blindness. Who – 24 patients. What – Whether or not stem cell therapy was effective
in treating Stargardt’s disease and/or dry age-related macular degeneration.
Population of interest – All people with these eye conditions.
20. Molten iron. Who – 10 castings at Cleveland Casting. What – The pouring
temperature (in degrees Fahrenheit) of molten iron. Population of interest – All
castings at Cleveland Casting.
21. Weighing bears. Who – 54 bears. What – Weight, neck size, length (no specified
units), and sex. When – Not specified. Where – Not specified. Why - Since bears are
difficult to weigh, the researchers hope to use the relationships between weight,
neck size, length, and sex of bears to estimate the weight of bears, given the other,
more observable features of the bear.
How – Researchers collected data on 54 bears they were able to catch.
