AB
YL
D
U
ST
, AB
YL
D
U
ST
,1-2 Chapter 1 Data and Decisions
conducted–survey; Variables–there are two categorical variables–what students think about whether or not
there will be more electric or gasoline powered vehicles in 2025 and the second categorical variable is also
ordinal–how likely, using a scale, would the student be to buy an electric vehicle in the next 10 years;
Source –the data are not from a designed survey or experiment; Type–the data are cross-sectional;
Concerns–none.
10. Your survey. Answers will vary.
11. World databank. Answers will vary but chosen from the following possible indicators:
GDP growth (annual %)
GDP (current US$)
GDP per capita (current US$)
GNI per capita, Atlas method (current US$)
Exports of goods and services (% of GDP)
ST
Foreign direct investment, net inflows (BoP, current US$)
GNI per capita, PPP (current international $)
GINI index
Inflation, consumer prices (annual %)
Population, total
Life expectancy at birth, total (years)
Internet users (per 100 people)
Imports of goods and services (% of GDP)
U
Unemployment, total (% of total labor force)
Agriculture, value added (% of GDP)
CO2 emissions (metric tons per capita)
Literacy rate, adult total (% of people ages 15 and above)
D
Central government debt, total (% of GDP)
Inflation, GDP deflator (annual %)
Poverty headcount ratio at national poverty line (% of population)
YL
12. 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–assess the nutritional value of the
different sandwiches; How–information was gathered from each of the sandwiches on the menu at Arby’s,
resulting in a census; Variables–there are 3 variables: the number of calories and serving size are
quantitative, and the type of meat is categorical; Source–data are not from a designed survey or experiment;
Type–data are cross-sectional; Concerns–none.
AB
13. MBA admissions. Who–MBA applicants (in northeastern U.S.); What–sex, age, whether or not accepted,
whether or not they attended, and the reasons for not attending (if they did not accept); When–not specified;
Where–a school in the northeastern United States; Why–the researchers wanted to investigate any patterns
in female student acceptance and attendance in the MBA program; How–data obtained from the admissions
office; Variables–there are 5 variables: sex, whether or not the students accepted, whether or not they
attended, and the reasons for not attending if they did not accept (all categorical) and age which is
quantitative; Source–data are not from a designed survey or experiment; Type–data are cross-sectional;
Concerns–none.
14. MBA admissions II. Who–MBA students (in program outside of Paris); What–each student’s standardized
test scores and GPA in the MBA program; When–2009 to 2014; Where–outside of Paris; Why–to
investigate the association between standardized test scores and performance in the MBA program over
five years (2009–2014); How–not specified; Variables–there are 2 quantitative variables: standardized test
scores and GPA; Source–data are not from a designed survey or experiment, data are available from student
records; Type–although the data are collected over 5 years, the purpose is to examine them as cross-
sectional rather than as time-series; Concerns–none.
Copyright © 2019 Pearson Education, Inc.
, Chapter 1 Data and Decisions 1-3
15. Pharmaceutical firm. Who–experimental volunteers; What–herbal cold remedy or sugar solution, and cold
severity; When–not specified; Where–major pharmaceutical firm; Why–scientists were testing the
effectiveness of an herbal compound on the severity of the common cold; How–scientists conducted a
controlled experiment; Variables–there are 2 variables: type of treatment (herbal or sugar solution) is
categorical, and severity rating is quantitative; Source – data come from an experiment; Type–data are
cross-sectional and from a designed experiment; Concerns–the severity of a cold might be difficult to
quantify (beneficial to add actual observations and measurements, such as body temperature). Also,
scientists at a pharmaceutical firm could have a predisposed opinion about the herbal solution or may feel
pressure to report negative findings about the herbal product.
16. Start-up company. Who–customers of a start-up company; What–customer name, ID number, region of
the country (coded as 1 = East, 2 = South, 3 = Midwest, 4 = West), date of last purchase, amount of
purchase ($), and item purchased; When–present day; Where–not specified; Why–the company is building a
database of customers and sales information; How–assumed that the company records the needed
information from each new customer; Variables–there are 6 variables: name, ID number, region of the
ST
country, and item purchased which are categorical and date and amount of purchase are quantitative. Date
could be coded as categorical as well; Source–data are not from a designed survey or experiment; Type–
data are cross-sectional; Concerns–although region is coded as a number, it is still a categorical variable.
17. Vineyards. Who–vineyards; What–size of vineyard (most likely in acres), number of years in existence,
state, varieties of grapes grown, average case price ($), gross sales ($), and percent profit; When–not
specified; Where–not specified; Why–business analysts hope to provide information that would be helpful
to producers of U.S. wines; How–questionnaire to a sample of growers; Variables–there are 5 quantitative
U
variables: the size of vineyard (acres), number of years in existence, average case price ($), gross sales ($);
there are 2 categorical variables: state and variety of grapes grown; Source–data come from a designed
survey; Type–data are cross-sectional; Concerns–none.
D
18. Spectrem group polls. Who–not completely clear. Probably a sample of affluent and retired people; What–
pet preference, number of pets, services and products bought for pets (from a list); When–not specified;
Where–United States; Why–provide services for the affluent; How–survey; Variables–there are 3
categorical variables: pet preference, list of pets and list of services and products bought for pet; Source–
YL
data from a designed survey; Type–data are cross-sectional; Concerns–none.
19. EPA. Who–every model of automobile in the United States; What–vehicle manufacturer, vehicle type (car,
SUV, etc.), weight (probably pounds), horsepower (units of horsepower), and gas mileage (miles per
gallon) for city and highway driving; When–the information is currently collected; Where–United States;
Why–the EPA uses the information to track fuel economy of vehicles; How– among the data EPA analysts
collect from the automobile manufacturers are the name of the manufacturer (Ford, Toyota, etc.), vehicle
type….”; Variables–there are 6 variables: vehicle manufacturer and vehicle type are categorical variables;
AB
weight, horsepower, and gas mileage for both city and highway driving are quantitative variables; Source–
data are not from a designed survey or experiment; Type–data are cross-sectional; Concerns–none.
20. Consumer Reports. Who–46 models of smart phones; What–brand, price (probably dollars), display size
(probably inches) operating system, camera image size (megapixels), and memory card slot (yes/no);
When–not specified; Where–not specified; Why–the information was compiled to provide information to
readers of Consumer Reports; How–not specified; Variables–– there are a total of 6 variables: price,
display size and image size are quantitative variables; brand and operating system are categorical variables,
and memory card slot is a nominal variable; Source–not specified; Type–the data are cross-sectional;
Concerns–this many or may not be a representative sample of smart phones, or includes all of them, we
don’t know. This is a rapidly changing market, so their data are at best a snapshot of the state of the market
at this time.
21. Zagat. Who–restaurants; What–% of customers liking restaurant, average meal cost ($), food rating (0-30),
decor rating (0-30), service rating (0-30); When–current; Where–not specified; Why–service to provide
information for consumers; How–not specified; Variables–there are 5 variables: % liking and average cost
Copyright © 2019 Pearson Education, Inc.
YL
D
U
ST
, AB
YL
D
U
ST
,1-2 Chapter 1 Data and Decisions
conducted–survey; Variables–there are two categorical variables–what students think about whether or not
there will be more electric or gasoline powered vehicles in 2025 and the second categorical variable is also
ordinal–how likely, using a scale, would the student be to buy an electric vehicle in the next 10 years;
Source –the data are not from a designed survey or experiment; Type–the data are cross-sectional;
Concerns–none.
10. Your survey. Answers will vary.
11. World databank. Answers will vary but chosen from the following possible indicators:
GDP growth (annual %)
GDP (current US$)
GDP per capita (current US$)
GNI per capita, Atlas method (current US$)
Exports of goods and services (% of GDP)
ST
Foreign direct investment, net inflows (BoP, current US$)
GNI per capita, PPP (current international $)
GINI index
Inflation, consumer prices (annual %)
Population, total
Life expectancy at birth, total (years)
Internet users (per 100 people)
Imports of goods and services (% of GDP)
U
Unemployment, total (% of total labor force)
Agriculture, value added (% of GDP)
CO2 emissions (metric tons per capita)
Literacy rate, adult total (% of people ages 15 and above)
D
Central government debt, total (% of GDP)
Inflation, GDP deflator (annual %)
Poverty headcount ratio at national poverty line (% of population)
YL
12. 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–assess the nutritional value of the
different sandwiches; How–information was gathered from each of the sandwiches on the menu at Arby’s,
resulting in a census; Variables–there are 3 variables: the number of calories and serving size are
quantitative, and the type of meat is categorical; Source–data are not from a designed survey or experiment;
Type–data are cross-sectional; Concerns–none.
AB
13. MBA admissions. Who–MBA applicants (in northeastern U.S.); What–sex, age, whether or not accepted,
whether or not they attended, and the reasons for not attending (if they did not accept); When–not specified;
Where–a school in the northeastern United States; Why–the researchers wanted to investigate any patterns
in female student acceptance and attendance in the MBA program; How–data obtained from the admissions
office; Variables–there are 5 variables: sex, whether or not the students accepted, whether or not they
attended, and the reasons for not attending if they did not accept (all categorical) and age which is
quantitative; Source–data are not from a designed survey or experiment; Type–data are cross-sectional;
Concerns–none.
14. MBA admissions II. Who–MBA students (in program outside of Paris); What–each student’s standardized
test scores and GPA in the MBA program; When–2009 to 2014; Where–outside of Paris; Why–to
investigate the association between standardized test scores and performance in the MBA program over
five years (2009–2014); How–not specified; Variables–there are 2 quantitative variables: standardized test
scores and GPA; Source–data are not from a designed survey or experiment, data are available from student
records; Type–although the data are collected over 5 years, the purpose is to examine them as cross-
sectional rather than as time-series; Concerns–none.
Copyright © 2019 Pearson Education, Inc.
, Chapter 1 Data and Decisions 1-3
15. Pharmaceutical firm. Who–experimental volunteers; What–herbal cold remedy or sugar solution, and cold
severity; When–not specified; Where–major pharmaceutical firm; Why–scientists were testing the
effectiveness of an herbal compound on the severity of the common cold; How–scientists conducted a
controlled experiment; Variables–there are 2 variables: type of treatment (herbal or sugar solution) is
categorical, and severity rating is quantitative; Source – data come from an experiment; Type–data are
cross-sectional and from a designed experiment; Concerns–the severity of a cold might be difficult to
quantify (beneficial to add actual observations and measurements, such as body temperature). Also,
scientists at a pharmaceutical firm could have a predisposed opinion about the herbal solution or may feel
pressure to report negative findings about the herbal product.
16. Start-up company. Who–customers of a start-up company; What–customer name, ID number, region of
the country (coded as 1 = East, 2 = South, 3 = Midwest, 4 = West), date of last purchase, amount of
purchase ($), and item purchased; When–present day; Where–not specified; Why–the company is building a
database of customers and sales information; How–assumed that the company records the needed
information from each new customer; Variables–there are 6 variables: name, ID number, region of the
ST
country, and item purchased which are categorical and date and amount of purchase are quantitative. Date
could be coded as categorical as well; Source–data are not from a designed survey or experiment; Type–
data are cross-sectional; Concerns–although region is coded as a number, it is still a categorical variable.
17. Vineyards. Who–vineyards; What–size of vineyard (most likely in acres), number of years in existence,
state, varieties of grapes grown, average case price ($), gross sales ($), and percent profit; When–not
specified; Where–not specified; Why–business analysts hope to provide information that would be helpful
to producers of U.S. wines; How–questionnaire to a sample of growers; Variables–there are 5 quantitative
U
variables: the size of vineyard (acres), number of years in existence, average case price ($), gross sales ($);
there are 2 categorical variables: state and variety of grapes grown; Source–data come from a designed
survey; Type–data are cross-sectional; Concerns–none.
D
18. Spectrem group polls. Who–not completely clear. Probably a sample of affluent and retired people; What–
pet preference, number of pets, services and products bought for pets (from a list); When–not specified;
Where–United States; Why–provide services for the affluent; How–survey; Variables–there are 3
categorical variables: pet preference, list of pets and list of services and products bought for pet; Source–
YL
data from a designed survey; Type–data are cross-sectional; Concerns–none.
19. EPA. Who–every model of automobile in the United States; What–vehicle manufacturer, vehicle type (car,
SUV, etc.), weight (probably pounds), horsepower (units of horsepower), and gas mileage (miles per
gallon) for city and highway driving; When–the information is currently collected; Where–United States;
Why–the EPA uses the information to track fuel economy of vehicles; How– among the data EPA analysts
collect from the automobile manufacturers are the name of the manufacturer (Ford, Toyota, etc.), vehicle
type….”; Variables–there are 6 variables: vehicle manufacturer and vehicle type are categorical variables;
AB
weight, horsepower, and gas mileage for both city and highway driving are quantitative variables; Source–
data are not from a designed survey or experiment; Type–data are cross-sectional; Concerns–none.
20. Consumer Reports. Who–46 models of smart phones; What–brand, price (probably dollars), display size
(probably inches) operating system, camera image size (megapixels), and memory card slot (yes/no);
When–not specified; Where–not specified; Why–the information was compiled to provide information to
readers of Consumer Reports; How–not specified; Variables–– there are a total of 6 variables: price,
display size and image size are quantitative variables; brand and operating system are categorical variables,
and memory card slot is a nominal variable; Source–not specified; Type–the data are cross-sectional;
Concerns–this many or may not be a representative sample of smart phones, or includes all of them, we
don’t know. This is a rapidly changing market, so their data are at best a snapshot of the state of the market
at this time.
21. Zagat. Who–restaurants; What–% of customers liking restaurant, average meal cost ($), food rating (0-30),
decor rating (0-30), service rating (0-30); When–current; Where–not specified; Why–service to provide
information for consumers; How–not specified; Variables–there are 5 variables: % liking and average cost
Copyright © 2019 Pearson Education, Inc.
