INSTRUCTOR’S SOLUTIONS MANUAL
INTRO STATS
6TH EDITION
CHAPTER NO. 1: STATS STARTS HERE
Section 1.1
1. Grocery shopping. Discount cards at grocery stores allow the stores to collect information
about the products that the customer purchases, what other products are purchased at the
same time, whether or not the customer uses coupons, and the date and time that the products
are purchased. This information can be linked to demographic information about the customer
that was volunteered when applying for the card, such as the customer’s name, address, sex,
age, income level, and other variables. The grocery store chain will use that information to
better market their products. This includes everything from printing coupons at the checkout
that are targeted to specific customers to deciding what television, print, or Internet
advertisements to use.
2. Online shopping. Amazon hopes to gain all sorts of information about customer behavior,
such as how long they spend looking at a page, whether or not they read reviews by other
customers, what items they ultimately buy, and what items are bought together. They can
then use this information to determine which other products to suggest to customers who buy
similar items, to determine which advertisements to run in the margins, and to determine
which items are the most popular so these items come up first in a search.
3. Parking lots. The owners of the parking garage can advertise about the availability of parking.
They can also communicate with businesses about hours when more spots are available and
when they should encourage more business.
4. Satellites and global climate change. This rise and fall of temperature and water levels can
help in planning for future problems and guide public policy to protect our safety.
Section 1.2
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. Grade level.
a) If we are, for example, comparing the percentage of first-graders who can tie their own
shoes to the percentage of second-graders who can tie their own shoes, grade-level is
treated as categorical. It is just a way to group the students. We would use the same
methods if we were comparing boys to girls or brown-eyed kids to blue-eyed kids.
b) If we were studying the relationship between grade-level and height, we would be treating
grade level as quantitative.
10. ZIP codes.
a) ZIP codes are categorical in the sense that they correspond to a location. The ZIP code
14850 is a standardized way of referring to Ithaca, NY.
b) ZIP codes generally increase as the location gets further from the east coast of the United
States. For example, one of the ZIP codes for the city of Boston, MA, is 02101. Kansas City,
MO, has a ZIP code of 64101, and Seattle, WA, has a ZIP code of 98101. But Honolulu, HI,
much further west than Seattle, has a ZIP code of 96701.
11. Gay marriage. The response is a categorical variable.
12. Gay marriage by party. The answer is a quantitative variable.
13. Medicine. The company is studying a quantitative variable.
14. Stress. The researcher is studying a quantitative variable.
Section 1.4
15. Voting and elections. Pollsters might consider whether a person voted previously or whether
he or she could name the candidates. Voting previously and knowing the candidates may
indicate a greater interest in the election.
16. Weather. Meteorologists can use the models to predict the average temperature ten days in
advance and compare their predictions to the actual temperatures.
17. The News. Answers will vary.
18. The Internet. Answers will vary.
19. Gaydar. Who – 40 undergraduate women. What – Whether or not the women could identify
the sexual orientation of men based on a picture. Population of interest – All women.
,20. Hula-hoops. Who – An unknown number of participants. What – Heart rate, oxygen
consumption, and rating of perceived exertion. Population of interest – All people.
21. Bicycle Safety. Who – 2,500 cars. What – Distance from the passing car to the bicycle (in
inches). Population of interest – All cars passing bicyclists.
22. Investments. Who – 30 similar companies. What – 401(k) employee participation rates (in
percent). Population of interest – All similar companies.
23. Honesty. Who – Workers who buy coffee in an office. What – amount of money
contributed to the collection tray. Population of interest – All people in honor system
payment situations.
24. Blindness. Who – 24 patients. What – Whether the patient had Stargardt’s disease or dry
age-related macular degeneration, and whether or not the stem cell therapy was effective in
treating the condition. Population of interest – All people with these eye conditions.
25. 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.
26. Molten iron. Who – 10 crankshafts at Cleveland Casting. What – The pouring temperature
(in degrees Fahrenheit) of molten iron. Population of interest – All crankshafts at Cleveland
Casting.
27. 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. Variables – There are
4 variables; weight, neck size, and length are quantitative variables, and sex is a categorical
variable. No units are specified for the quantitative variables. Concerns – The researchers
are (obviously!) only able to collect data from bears they were able to catch. This method is
a good one, as long as the researchers believe the bears caught are representative of all
bears with regard to the relationships between weight, neck size, length, and sex.
28. Schools. Who – Students. What – Age (probably in years, though perhaps in years and
months), race or ethnicity, number of absences, grade level, reading score, math score, and
disabilities/special needs. When – This information must be kept current. Where – Not
specified. Why – Keeping this information is a state requirement. How – The information is
collected and stored as part of school records. Variables – There are seven variables. Race
or ethnicity, grade level, and disabilities/special needs are categorical variables. Number
of absences (days), age (years?), reading test score, and math test score are quantitative
variables. Concerns – What tests are used to measure reading and math ability, and what
are the units of measure for the tests?
, 29. Arby’s menu. Who – Arby’s sandwiches. What – type of meat, number of calories (in
calories), and serving size (in ounces). When – Not specified. Where – Arby’s restaurants.
Why – These data might be used to assess the nutritional value of the different sandwiches.
How –Information was gathered from each of the sandwiches on the menu at Arby’s.
Variables –There are three variables. Number of calories (calories) and serving size (ounces)
are quantitative variables, and type of meat is a categorical variable.
30. Religious Landscape. Who – U.S. Adults. What – Age, Gender, Education, Marital Status,
Belief in God (certain, fairly certain, not certain, don’t know, do not believe in God), and
Frequency of Prayer (daily, weekly, monthly, seldom/never). When –2014. Where – United
States. Why – The information was gathered for presentation in the Pew Research Center
2014 Religious Landscape study. How – Not specified. Variables – There are six variables.
Gender, Marital status, Belief in God, Frequency of Prayer are categorical variables; Age
(years) is a quantitative variable. Education could be quantitative (measured in years) or
categorical if specified in levels rather than number of years.
31. E-bikes. Who – Electric bicycles. What – motor size (in watts), maximum speed (mph),
wheel base (mm), brand name, whether the battery can be removed for security. When – May
2020. Where – no location specified. Why – Bicycling magazine review. How – Not specified.
Variables – There are three quantitative variables: Motor size, maximum speed, wheel base.
There are two categorical variables: Brand and whether the battery can be removed.
32. Flowers. Who – 385 species of flowers. What – Date of first flowering (in days). When – Not
specified. Where – Southern England. Why – The researchers believe that this indicates a
warming of the overall climate. How – Not specified. Variables – Date of first flowering is a
quantitative variable. Concerns - Hopefully, date of first flowering was measured in days
from January 1, or some other convention, to avoid problems with leap years.
33. Herbal medicine. Who – experiment volunteers. What – herbal cold remedy or sugar
solution, and cold severity (0 to 5 scale). When – Not specified. Where – Major
pharmaceutical firm. Why – Scientists were testing the efficacy of an herbal compound on
the severity of the common cold. How – The scientists set up a controlled experiment.
Variables – There are two variables. Type of treatment (herbal or sugar solution) is
categorical, and severity rating is quantitative. Concerns – The severity of a cold seems
subjective and difficult to quantify. Also, the scientists may feel pressure to report negative
findings about the herbal product.
34. Vineyards. Who – American vineyards. What – Size of vineyard (in acres), number of years
in existence, state, varieties of grapes grown, average case price (in dollars), gross sales
(probably in dollars), and percent profit. When – Not specified. Where – United States. Why
– Business analysts hoped to provide information that would be helpful to producers of
American wines. How – Not specified. Variables – There are five quantitative variables and
two categorical variables. Size of vineyard, number of years in existence, average case price,
gross sales, and percent profit are quantitative variables. State and variety of grapes grown
are categorical variables.
INTRO STATS
6TH EDITION
CHAPTER NO. 1: STATS STARTS HERE
Section 1.1
1. Grocery shopping. Discount cards at grocery stores allow the stores to collect information
about the products that the customer purchases, what other products are purchased at the
same time, whether or not the customer uses coupons, and the date and time that the products
are purchased. This information can be linked to demographic information about the customer
that was volunteered when applying for the card, such as the customer’s name, address, sex,
age, income level, and other variables. The grocery store chain will use that information to
better market their products. This includes everything from printing coupons at the checkout
that are targeted to specific customers to deciding what television, print, or Internet
advertisements to use.
2. Online shopping. Amazon hopes to gain all sorts of information about customer behavior,
such as how long they spend looking at a page, whether or not they read reviews by other
customers, what items they ultimately buy, and what items are bought together. They can
then use this information to determine which other products to suggest to customers who buy
similar items, to determine which advertisements to run in the margins, and to determine
which items are the most popular so these items come up first in a search.
3. Parking lots. The owners of the parking garage can advertise about the availability of parking.
They can also communicate with businesses about hours when more spots are available and
when they should encourage more business.
4. Satellites and global climate change. This rise and fall of temperature and water levels can
help in planning for future problems and guide public policy to protect our safety.
Section 1.2
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. Grade level.
a) If we are, for example, comparing the percentage of first-graders who can tie their own
shoes to the percentage of second-graders who can tie their own shoes, grade-level is
treated as categorical. It is just a way to group the students. We would use the same
methods if we were comparing boys to girls or brown-eyed kids to blue-eyed kids.
b) If we were studying the relationship between grade-level and height, we would be treating
grade level as quantitative.
10. ZIP codes.
a) ZIP codes are categorical in the sense that they correspond to a location. The ZIP code
14850 is a standardized way of referring to Ithaca, NY.
b) ZIP codes generally increase as the location gets further from the east coast of the United
States. For example, one of the ZIP codes for the city of Boston, MA, is 02101. Kansas City,
MO, has a ZIP code of 64101, and Seattle, WA, has a ZIP code of 98101. But Honolulu, HI,
much further west than Seattle, has a ZIP code of 96701.
11. Gay marriage. The response is a categorical variable.
12. Gay marriage by party. The answer is a quantitative variable.
13. Medicine. The company is studying a quantitative variable.
14. Stress. The researcher is studying a quantitative variable.
Section 1.4
15. Voting and elections. Pollsters might consider whether a person voted previously or whether
he or she could name the candidates. Voting previously and knowing the candidates may
indicate a greater interest in the election.
16. Weather. Meteorologists can use the models to predict the average temperature ten days in
advance and compare their predictions to the actual temperatures.
17. The News. Answers will vary.
18. The Internet. Answers will vary.
19. Gaydar. Who – 40 undergraduate women. What – Whether or not the women could identify
the sexual orientation of men based on a picture. Population of interest – All women.
,20. Hula-hoops. Who – An unknown number of participants. What – Heart rate, oxygen
consumption, and rating of perceived exertion. Population of interest – All people.
21. Bicycle Safety. Who – 2,500 cars. What – Distance from the passing car to the bicycle (in
inches). Population of interest – All cars passing bicyclists.
22. Investments. Who – 30 similar companies. What – 401(k) employee participation rates (in
percent). Population of interest – All similar companies.
23. Honesty. Who – Workers who buy coffee in an office. What – amount of money
contributed to the collection tray. Population of interest – All people in honor system
payment situations.
24. Blindness. Who – 24 patients. What – Whether the patient had Stargardt’s disease or dry
age-related macular degeneration, and whether or not the stem cell therapy was effective in
treating the condition. Population of interest – All people with these eye conditions.
25. 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.
26. Molten iron. Who – 10 crankshafts at Cleveland Casting. What – The pouring temperature
(in degrees Fahrenheit) of molten iron. Population of interest – All crankshafts at Cleveland
Casting.
27. 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. Variables – There are
4 variables; weight, neck size, and length are quantitative variables, and sex is a categorical
variable. No units are specified for the quantitative variables. Concerns – The researchers
are (obviously!) only able to collect data from bears they were able to catch. This method is
a good one, as long as the researchers believe the bears caught are representative of all
bears with regard to the relationships between weight, neck size, length, and sex.
28. Schools. Who – Students. What – Age (probably in years, though perhaps in years and
months), race or ethnicity, number of absences, grade level, reading score, math score, and
disabilities/special needs. When – This information must be kept current. Where – Not
specified. Why – Keeping this information is a state requirement. How – The information is
collected and stored as part of school records. Variables – There are seven variables. Race
or ethnicity, grade level, and disabilities/special needs are categorical variables. Number
of absences (days), age (years?), reading test score, and math test score are quantitative
variables. Concerns – What tests are used to measure reading and math ability, and what
are the units of measure for the tests?
, 29. Arby’s menu. Who – Arby’s sandwiches. What – type of meat, number of calories (in
calories), and serving size (in ounces). When – Not specified. Where – Arby’s restaurants.
Why – These data might be used to assess the nutritional value of the different sandwiches.
How –Information was gathered from each of the sandwiches on the menu at Arby’s.
Variables –There are three variables. Number of calories (calories) and serving size (ounces)
are quantitative variables, and type of meat is a categorical variable.
30. Religious Landscape. Who – U.S. Adults. What – Age, Gender, Education, Marital Status,
Belief in God (certain, fairly certain, not certain, don’t know, do not believe in God), and
Frequency of Prayer (daily, weekly, monthly, seldom/never). When –2014. Where – United
States. Why – The information was gathered for presentation in the Pew Research Center
2014 Religious Landscape study. How – Not specified. Variables – There are six variables.
Gender, Marital status, Belief in God, Frequency of Prayer are categorical variables; Age
(years) is a quantitative variable. Education could be quantitative (measured in years) or
categorical if specified in levels rather than number of years.
31. E-bikes. Who – Electric bicycles. What – motor size (in watts), maximum speed (mph),
wheel base (mm), brand name, whether the battery can be removed for security. When – May
2020. Where – no location specified. Why – Bicycling magazine review. How – Not specified.
Variables – There are three quantitative variables: Motor size, maximum speed, wheel base.
There are two categorical variables: Brand and whether the battery can be removed.
32. Flowers. Who – 385 species of flowers. What – Date of first flowering (in days). When – Not
specified. Where – Southern England. Why – The researchers believe that this indicates a
warming of the overall climate. How – Not specified. Variables – Date of first flowering is a
quantitative variable. Concerns - Hopefully, date of first flowering was measured in days
from January 1, or some other convention, to avoid problems with leap years.
33. Herbal medicine. Who – experiment volunteers. What – herbal cold remedy or sugar
solution, and cold severity (0 to 5 scale). When – Not specified. Where – Major
pharmaceutical firm. Why – Scientists were testing the efficacy of an herbal compound on
the severity of the common cold. How – The scientists set up a controlled experiment.
Variables – There are two variables. Type of treatment (herbal or sugar solution) is
categorical, and severity rating is quantitative. Concerns – The severity of a cold seems
subjective and difficult to quantify. Also, the scientists may feel pressure to report negative
findings about the herbal product.
34. Vineyards. Who – American vineyards. What – Size of vineyard (in acres), number of years
in existence, state, varieties of grapes grown, average case price (in dollars), gross sales
(probably in dollars), and percent profit. When – Not specified. Where – United States. Why
– Business analysts hoped to provide information that would be helpful to producers of
American wines. How – Not specified. Variables – There are five quantitative variables and
two categorical variables. Size of vineyard, number of years in existence, average case price,
gross sales, and percent profit are quantitative variables. State and variety of grapes grown
are categorical variables.
