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## Test Bank Business Statistics A First Course, 8th Edition David M. Levine A+

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Test Bank Business Statistics A First Course, 8th Edition David M. Levine A+
1. The process of using data collected from a small group to reach conclusions about a large group is called

a) statistical inference.

b) DCOVA framework.

c) operational definition.

d) descriptive statistics.

ANSWER:

a

TYPE: MC DIFFICULTY: Easy

KEYWORDS: inferential statistics

1. Those methods involving the collection, presentation, and characterization of a set of data in order to properly describe the various features of that set of data are called

a) statistical inference.

b) DCOVA framework.

c) operational definition.

d) descriptive statistics.

ANSWER:

d

TYPE: MC DIFFICULTY: Easy

KEYWORDS: descriptive statistics

1. The collection and summarization of the socioeconomic and physical characteristics of the employees of a particular firm is an example of

a) inferential statistics.

b) descriptive statistics.

c) operational definition.

d) DCOVA framework.

ANSWER:

b

TYPE: MC DIFFICULTY: Easy

KEYWORDS: descriptive statistics

1. The estimation of the population average family expenditure on food based on the sample average expenditure of 1,000 families is an example of

a) inferential statistics.

b) descriptive statistics.

c) DCOVA framework.

d) operational definition.

ANSWER:

a

TYPE: MC DIFFICULTY: Easy

KEYWORDS: inferential statistics

1. Which of the following is not an element of descriptive statistical problems?

a) An inference made about the population based on the sample.

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First Thing First 2

b) The population or sample of interest.

c) Tables, graphs, or numerical summary tools.

d) Identification of patterns in the data.

ANSWER:

a

TYPE: MC DIFFICULTY: Moderate

KEYWORDS: descriptive statistics

1. A study is under way in Yosemite National Forest to determine the adult height of American pine trees. Specifically, the study is attempting to determine what factors aid a tree in reaching heights greater than 60 feet tall. It is estimated that the forest contains 25,000 adult American pines. The study involves collecting heights from 250 randomly selected adult American pine trees and analyzing the results. Identify the variable of interest in the study.

a) The age of an American pine tree in Yosemite National Forest.

b) The height of an adult American pine tree in Yosemite National Forest.

c) The number of American pine trees in Yosemite National Forest.

d) The species of trees in Yosemite National Forest.

ANSWER:

b

TYPE: MC DIFFICULTY: Easy

KEYWORDS: variable

1. Most analysts focus on the cost of tuition as the way to measure the cost of a college education. But incidentals, such as textbook costs, are rarely considered. A researcher at Drummand University wishes to estimate the textbook costs of first-year students at Drummand. To do so, she monitored the textbook cost of 250 first-year students and found that their average textbook cost was \$600 per semester. Identify the variable of interest to the researcher.

a) The textbook cost of first-year Drummand University students.

b) The year in school of Drummand University students.

c) The age of Drummand University students.

d) The cost of incidental expenses of Drummand University students.

ANSWER:

a

TYPE: MC DIFFICULTY: Easy

KEYWORDS: variable

1. True or False: Problems may arise when statistically unsophisticated users who do not understand the assumptions behind the statistical procedures or their limitations are misled by results obtained from computer software.

ANSWER:

True

TYPE: TF DIFFICULTY: Easy

KEYWORDS: statistical package

1. True or False: Managers need an understanding of statistics to be able to present and describe information accurately, draw conclusions about large populations based on small samples, improve processes, and make reliable forecasts.

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First Thing First 3

ANSWER:

True

TYPE: TF DIFFICULTY: Easy

KEYWORDS: reasons for learning statistics

1. True or False: A professor computed the sample average exam score of 20 students and used it to estimate the average exam score of the 1,500 students taking the exam. This is an example of inferential statistics.

ANSWER:

True

TYPE: TF DIFFICULTY: Easy

KEYWORDS: descriptive statistics, inferential statistics

1. True or False: Using the number of registered voters who turned out to vote for the primary in Iowa to predict the number of registered voters who will turn out to vote in Vermont’s primary is an example of descriptive statistics.

ANSWER:

False

TYPE: TF DIFFICULTY: Easy

KEYWORDS: descriptive statistics, inferential statistics

1. True or False: Compiling the number of registered voters who turned out to vote for the primary in Iowa is an example of descriptive statistics.

ANSWER:

True

TYPE: TF DIFFICULTY: Easy

KEYWORDS: descriptive statistics, inferential statistics

1. The Human Resources Director of a large corporation wishes to develop an employee benefits package and decides to select 500 employees from a list of all (N = 40,000) workers in order to study their preferences for the various components of a potential package. In this study, methods involving the collection, presentation, and characterization of the data are called .

ANSWER:

descriptive statistics/methods TYPE: FI DIFFICULTY: Easy

KEYWORDS: descriptive statistics

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First Thing First 4

1. The Human Resources Director of a large corporation wishes to develop an employee benefits package and decides to select 500 employees from a list of all (N = 40,000) workers in order to study their preferences for the various components of a potential package. In this study, methods that result in decisions concerning population characteristics based only on the sample results are called.

ANSWER:

inferential statistics/methods TYPE: FI DIFFICULTY: Easy

KEYWORDS: inferential statistics

1. The oranges grown in corporate farms in an agricultural state were damaged by some unknown fungi a few years ago. Suppose the manager of a large farm wanted to study the impact of the fungi on the orange crops on a daily basis over a 6-week period. On each day a random sample of orange trees was selected from within a random sample of acres. The daily average number of damaged oranges per tree and the proportion of trees having damaged oranges were calculated. In this study, drawing conclusions on any one day about the true population characteristics based on information obtained from the sample is called .

ANSWER:

inferential statistics/methods TYPE: FI DIFFICULTY: Moderate

KEYWORDS: inferential statistics

1. The oranges grown in corporate farms in an agricultural state were damaged by some unknown fungi a few years ago. Suppose the manager of a large farm wanted to study the impact of the fungi on the orange crops on a daily basis over a 6-week period. On each day a random sample of orange trees was selected from within a random sample of acres. The daily average number of damaged oranges per tree and the proportion of trees having damaged oranges were calculated. In this study, the presentation and characterization of the two main measures calculated each day (i.e., average number of damaged oranges per tree and proportion of trees having damaged oranges) is called .

ANSWER:

descriptive statistics/methods TYPE: FI DIFFICULTY: Moderate

KEYWORDS: descriptive statistics

1. The Commissioner of Health in New York State wanted to study malpractice litigation in New York. A sample of 31 thousand medical records was drawn from a population of 2.7 million patients who were discharged during 2010. Using the information obtained from the sample to predict population characteristics with respect to malpractice litigation is an example of .

ANSWER:

inferential statistics

TYPE: FI DIFFICULTY: Moderate

KEYWORDS: inferential statistics

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First Thing First 5

1. The Commissioner of Health in New York State wanted to study malpractice litigation in New York. A sample of 31 thousand medical records was drawn from a population of 2.7 million patients who were discharged during 2010. The collection, presentation, and characterization of the data from patient medical records are examples of .

ANSWER:

descriptive statistics/methods TYPE: FI DIFFICULTY: Easy

KEYWORDS: descriptive statistics

1. True or False: Business analytics combine “traditional” statistical methods with methods and techniques from management science and information systems to form an interdisciplinary tool that supports fact-based management decision making.

ANSWER:

True

TYPE: TF DIFFICULTY: Easy

KEYWORDS: business analytics

1. Which of the following is not true about business analytics?

a) It enables you to use statistical methods to analyze and explore data to uncover unforeseen relationships.

b) It enables you to use management science methods to develop optimization models that impact an organization’s strategy, planning, and operations.

c) It enables you to use complex mathematics to replace the need for organizational decision making and problem solving.

d) It enables you to use information systems methods to collect and process data sets of all sizes.

ANSWER:

c

TYPE: MC DIFFICULTY: Moderate

KEYWORDS: business analytics

1. True or False: “Big data” is a concrete concept with a precise operational definition.

ANSWER:

False

TYPE: TF DIFFICULTY: Easy

KEYWORDS: big data

1. True or False: “Big data” are data being collected in huge volumes and at very fast rates, and they typically arrive in a variety of forms, organized and unorganized.

ANSWER:

True

TYPE: TF DIFFICULTY: Easy

KEYWORDS: big data

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First Thing First 6

1. True or False: In the current data-driven environment of business, the decisions you make will be increasingly based on gut or intuition supported by personal experience.

ANSWER:

False

TYPE: TF DIFFICULTY: Easy

KEYWORDS: business analytics

1. True or False: The D in the DCOVA framework stands for “data”.

ANSWER:

False

TYPE: TF DIFFICULTY: Easy

KEYWORDS: DCOVA framework

1. True or False: The D in the DCOVA framework stands for “define”.

ANSWER:

True

TYPE: TF DIFFICULTY: Easy

KEYWORDS: DCOVA framework

1. True or False: The C in the DCOVA framework stands for “categorize”.

ANSWER:

False

TYPE: TF DIFFICULTY: Easy

KEYWORDS: DCOVA framework

1. True or False: The C in the DCOVA framework stands for “collect”.

ANSWER:

True

TYPE: TF DIFFICULTY: Easy

KEYWORDS: DCOVA framework

1. True or False: The O in the DCOVA framework stands for “operationalize”.

ANSWER:

False

TYPE: TF DIFFICULTY: Easy

KEYWORDS: DCOVA framework

1. True or False: The O in the DCOVA framework stands for “organize”.

ANSWER:

True

TYPE: TF DIFFICULTY: Easy

KEYWORDS: DCOVA framework

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First Thing First 7

1. True or False: The V in the DCOVA framework stands for “verify”.

ANSWER:

False

TYPE: TF DIFFICULTY: Easy

KEYWORDS: DCOVA framework

1. True or False: The V in the DCOVA framework stands for “visualize”.

ANSWER:

True

TYPE: TF DIFFICULTY: Easy

KEYWORDS: DCOVA framework

1. True or False: The A in the DCOVA framework stands for “apply”.

ANSWER:

False

TYPE: TF DIFFICULTY: Easy

KEYWORDS: DCOVA framework

1. True or False: The V in the DCOVA framework stands for “value”.

ANSWER:

False

TYPE: TF DIFFICULTY: Easy

KEYWORDS: DCOVA framework

1. Which of the following is not an attribute of big data?

1. Variegated
1. Velocity
2. Volume
1. Variety

ANSWER:

a

TYPE: TF DIFFICULTY: Easy

KEYWORDS: business analytics

1. True or False: If rising temperatures are followed immediately by an increase in crime in urban areas, we would attribute the two events to be an instance of logical causality.

ANSWER:

False

TYPE: TF DIFFICULTY: Moderate

KEYWORDS: Starting points for learning statistics, page 6 text.

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First Thing First 8

1. True or False: Because of its irregular pattern and the fact it must be collected by irregular means, unstructured data is not a type of big data.

ANSWER:

False

TYPE: TF DIFFICULTY: Moderate

KEYWORDS: FTF2 Business Analytics: The Changing Face of Statistics, page 4 text.

1. Which of the following types of software can store dashboards?
1. Minitab
1. Both Minitab and Tableau
2. Tableau
1. Excel and Minitab

ANSWER:

c

TYPE: MC DIFFICULTY: Easy

KEYWORDS: business analytics, software

1. Which of the following is not a good practice for using software properly?
1. Using preexisting solutions to solve new problems
1. Using generic names to identify applications such as Assignment01, Assignment02, etc.
2. Always build solutions from scratch.
1. b and c

ANSWER:

d

TYPE: MC DIFFICULTY: Moderate

KEYWORDS: business analytics, software

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Defining and Collecting Data 1-1

# CHAPTER 1: DEFINING AND COLLECTING DATA

1. Which of the following is a discrete quantitative (numerical) variable?

a) The Dow Jones Industrial average

b) The volume of water released from a dam

c) The distance you drove yesterday.

d) The number of employees of an insurance company

ANSWER:

d

TYPE: MC DIFFICULTY: Easy

KEYWORDS: discrete variable, types of data

1. Which of the following is a continuous quantitative (numerical) variable?

a) The color of a student’s eyes

b) The number of employees of an insurance company

c) The amount of milk in a 2-liter carton.

d) The number of gallons of milk sold at the local grocery store yesterday

ANSWER:

c

TYPE: MC DIFFICULTY: Easy

KEYWORDS: continuous variable, types of data

1. To monitor campus security, the campus police office is taking a survey of the number of students in a parking lot each 30 minutes of a 24-hour period with the goal of determining when patrols of the lot would serve the most students. If X is the number of students in the lot each period, then X is an example of

a) a categorical variable.

b) a discrete variable.

c) a continuous variable.

d) a statistic.

ANSWER:

b

TYPE: MC DIFFICULTY: Moderate

KEYWORDS: discrete variable, types of data

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1-2 Defining and Collecting Data

1. Researchers are concerned that the weight of the average American school child is increasing implying, among other things, that children’s clothing should be manufactured and marketed in larger sizes. If X is the weight of school children sampled in a nationwide study without rounding, then X is an example of

a) a categorical variable.

b) a discrete variable.

c) a continuous variable.

d) a table of random numbers.

ANSWER:

c

TYPE: MC DIFFICULTY: Moderate

KEYWORDS: continuous variable, types of data

1. The classification of student class designation (freshman, sophomore, junior, senior) is an example of

a) a categorical variable.

b) a discrete variable.

c) a continuous variable.

d) a table of random numbers.

ANSWER:

a

TYPE: MC DIFFICULTY: Easy

KEYWORDS: categorical variable, types of data

1. The classification of student major (accounting, economics, management, marketing, other) is an example of

a) a categorical variable.

b) a discrete variable.

c) a continuous variable.

d) a table of random numbers.

ANSWER:

a

TYPE: MC DIFFICULTY: Easy

KEYWORDS: categorical variable, types of data

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Defining and Collecting Data 1-3

1. The chancellor of a major university was concerned about alcohol abuse on her campus and wanted to find out the proportion of students at her university who visited campus bars on the weekend before the final exam week. Her assistant took a random sample of 250 students. The answer on “whether you visited campus bars on the weekend before the final exam week” from students in the sample is an example of .

a) a categorical variable.

b) a discrete variable.

c) a continuous variable.

d) a table of random numbers.

ANSWER:

a

TYPE: MC DIFFICULTY: Easy

KEYWORDS: categorical variable, types of data SCENARIO 1-1

The manager of the customer service division of a major consumer electronics company is interested in determining whether the customers who have purchased a Blu-ray player made by the company over the past 12 months are satisfied with their products.

1. Referring to Scenario 1-1, the possible responses to the question "How many Blu-ray players made by other manufacturers have you used?" are values from a

a) discrete variable.

b) continuous variable.

c) categorical variable.

d) table of random numbers.

ANSWER:

a

TYPE: MC DIFFICULTY: Easy

KEYWORDS: discrete variable, types of data

1. Referring to Scenario 1-1, the possible responses to the question "Are you happy, indifferent, or unhappy with the performance per dollar spent on the Blu-ray player?" are values from a

a) discrete numerical variable.

b) continuous numerical variable.

c) categorical variable.

d) table of random numbers.

ANSWER:

c

TYPE: MC DIFFICULTY: Easy

KEYWORDS: categorical variable, types of data

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1-4 Defining and Collecting Data

1. Referring to Scenario 1-1, the possible responses to the question "What is your annual income rounded to the nearest thousands?" are values from a

a) discrete numerical variable.

b) continuous numerical variable.

c) categorical variable.

d) table of random numbers.

ANSWER:

a

TYPE: MC DIFFICULTY: Difficult

KEYWORDS: discrete variable, types of data

EXPLANATION: Even though money is usually considered as a continuous variable, it should be considered as a discrete variable when rounded to the nearest thousands.

1. Referring to Scenario 1-1, the possible responses to the question "How much time do you use the Blu-ray player every week on the average?" are values from a

a) discrete numerical variable.

b) continuous numerical variable.

c) categorical variable.

d) table of random numbers.

ANSWER:

b

TYPE: MC DIFFICULTY: Easy

KEYWORDS: continuous variable, types of data

1. Referring to Scenario 1-1, the possible responses to the question "How many people are there in your household?" are values from a

a) discrete numerical variable.

b) continuous numerical variable.

c) categorical variable.

d) table of random numbers.

ANSWER:

a

TYPE: MC DIFFICULTY: Easy

KEYWORDS: discrete variable, types of data

1. Referring to Scenario 1-1, the possible responses to the question "How would you rate the quality of your purchase experience with 1 = excellent, 2 = good, 3 = decent, 4 = poor, 5 = terrible?" are values from a

a) discrete numerical variable.

b) continuous numerical variable.

c) categorical variable.

d) table of random numbers.

ANSWER:

c

TYPE: MC DIFFICULTY: Easy

KEYWORDS: categorical variable, types of data

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Defining and Collecting Data 1-5

1. Referring to Scenario 1-1, the possible responses to the question "What brand of Blu-ray player did you purchase?" are values from a

a) discrete numerical variable.

b) continuous numerical variable.

c) categorical variable.

d) table of random numbers.

ANSWER:

c

TYPE: MC DIFFICULTY: Easy

KEYWORDS: categorical variable, types of data

1. Referring to Scenario 1-1, the possible responses to the question "Out of a 100-point score with 100 being the highest and 0 being the lowest, what is your satisfaction level on the videocassette recorder that you purchased?" are values from a

a) discrete numerical variable.

b) continuous numerical variable.

c) categorical variable.

d) table of random numbers.

ANSWER:

a

TYPE: MC DIFFICULTY: Moderate

KEYWORDS: discrete variable, types of data

1. Referring to Scenario 1-1, the possible responses to the question "In which year were you born?" are values from a

a) discrete numerical variable.

b) continuous numerical variable.

c) categorical variable.

d) table of random numbers.

ANSWER:

a

TYPE: MC DIFFICULTY: Moderate

KEYWORDS: discrete variable, types of data

1. Referring to Scenario 1-1, the possible responses to the question "How many Blu-ray players made by other manufacturers have you used? “results in

a) a nominal scale variable.

b) an ordinal scale variable.

c) an interval scale variable.

d) a ratio scale variable.

ANSWER:

d

TYPE: MC DIFFICULTY: Moderate

KEYWORDS: ratio scale, types of data

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1-6 Defining and Collecting Data

1. Referring to Scenario 1-1, the possible responses to the question "Are you happy, indifferent, or unhappy with the performance per dollar spent on the Blu-ray player?" result in

a) a nominal scale variable.

b) an ordinal scale variable.

c) an interval scale variable.

d) a ratio scale variable.

ANSWER:

b

TYPE: MC DIFFICULTY: Moderate

KEYWORDS: ordinal scale, types of data

1. Referring to Scenario 1-1, the possible responses to the question "What is your annual income rounded to the nearest thousands?" result in

a) a nominal scale variable.

b) an ordinal scale variable.

c) an interval scale variable.

d) a ratio scale variable.

ANSWER:

d

TYPE: MC DIFFICULTY: Moderate

KEYWORDS: ratio scale, types of data

1. Referring to Scenario 1-1, the possible responses to the question "How much time do you use the Blu-ray player every week on the average?" result in

a) a nominal scale variable.

b) an ordinal scale variable.

c) an interval scale variable.

d) a ratio scale variable.

ANSWER:

d

TYPE: MC DIFFICULTY: Moderate

KEYWORDS: ratio scale, types of data

1. Referring to Scenario 1-1, the possible responses to the question "How many people are there in your household?" result in

a) a nominal scale variable.

b) an ordinal scale variable.

c) an interval scale variable.

d) a ratio scale variable.

ANSWER:

d

TYPE: MC DIFFICULTY: Moderate

KEYWORDS: ratio scale, types of data

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Defining and Collecting Data 1-7

1. Referring to Scenario 1-1, the possible responses to the question "How would you rate the quality of your purchase experience with 1 = excellent, 2 = good, 3 = decent, 4 = poor, 5 = terrible?" result in

a) a nominal scale variable.

b) an ordinal scale variable.

c) an interval scale variable.

d) a ratio scale variable.

ANSWER:

b

TYPE: MC DIFFICULTY: Moderate

EXPLANATION: The rating is ordinal scale not an interval scale because the difference in rating between “excellent” and “good” does not have to be the same as the difference between “poor” and “terrible”.

KEYWORDS: ordinal scale, types of data

1. Referring to Scenario 1-1, the possible responses to the question "What brand of Blu-ray player did you purchase?" result in

a) a nominal scale variable.

b) an ordinal scale variable.

c) an interval scale variable.

d) a ratio scale variable.

ANSWER:

a

TYPE: MC DIFFICULTY: Easy

KEYWORDS: nominal scale, types of data

1. Referring to Scenario 1-1, the possible responses to the question "Out of a 100-point score with 100 being the highest and 0 being the lowest, what is your satisfaction level with the Blu-ray player that you purchased results in:

a) a nominal scale variable.

b) an ordinal scale variable.

c) an interval scale variable.

d) a ratio scale variable.

ANSWER:

c

TYPE: MC DIFFICULTY: Difficult

EXPLANATION: The rating is interval scale not ordinal scale because the difference in rating between “80” and “90” can be treated as the same as the difference between “30” and “40” but a rating of “80” does not imply twice the level of satisfaction level as a rating of “40”.

KEYWORDS: interval scale, types of data

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1-8 Defining and Collecting Data

1. Referring to Scenario 1-1, the possible responses to the question "What is your age at last birthday ?” results in:

a) a nominal scale variable.

b) an ordinal scale variable.

c) an interval scale variable.

d) a ratio scale variable.

ANSWER:

d- A 40-year-old is twice as old as a 20-year-old TYPE: MC DIFFICULTY: Difficult

KEYWORDS: interval scale, types of data

1. True or False: The possible responses to the question “How long have you been living at your current residence?” are values from a continuous variable.

ANSWER:

True

TYPE: TF DIFFICULTY: Moderate

KEYWORDS: continuous variable, types of data

1. True or False: The possible responses to the question “How many times in the past three months have you visited a city park?” are values from a discrete variable.

ANSWER:

True

TYPE: TF DIFFICULTY: Moderate

KEYWORDS: discrete variable, types of data

1. True or False: A continuous variable may take on any value within its relevant range even though the measurement device may not be precise enough to record it.

ANSWER:

True

TYPE: TF DIFFICULTY: Moderate

KEYWORDS: continuous variable, types of data

1. True or False: Faculty rank (professor to lecturer) is an example of discrete numerical data.

ANSWER:

False

TYPE: TF DIFFICULTY: Easy

KEYWORDS: categorical variable, types of data

1. True or False: Student grades (A to F) are an example of continuous numerical data.

ANSWER:

False

TYPE: TF DIFFICULTY: Moderate

KEYWORDS: categorical variables, types of data

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Defining and Collecting Data 1-9

1. True or False: The amount of coffee consumed by an individual in a day is an example of a discrete numerical variable.

ANSWER:

False

TYPE: TF DIFFICULTY: Moderate

KEYWORDS: continuous variables, types of data

1. True or False: The answer to the question “What is your favorite color?” is an example of an ordinal scaled variable.

ANSWER:

False

TYPE: TF DIFFICULTY: Easy

KEYWORDS: nominal scale

1. True or False: The answer to the question “How do you rate the quality of your business statistics course” is an example of an ordinal scaled variable.

ANSWER:

True

TYPE: TF DIFFICULTY: Easy

KEYWORDS: ordinal scale

1. True or False: The answer to the question “How many hours on average do you spend watching TV every week?” is an example of a ratio scaled variable.

ANSWER:

True

TYPE: TF DIFFICULTY: Easy

KEYWORDS: ratio scale

1. True or False: The answer to the question “What is your sleeping bag temperature rating?” is an example of a ratio scaled variable.

ANSWER:

False

TYPE: TF DIFFICULTY: Easy

KEYWORDS: interval scale

1. An insurance company evaluates many numerical variables about a person before deciding on an appropriate rate for automobile insurance. The number of claims a person has made in the last 3 years is an example of a numerical variable.

ANSWER:

discrete

TYPE: FI DIFFICULTY: Easy

KEYWORDS: discrete variable, types of data

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1-10 Defining and Collecting Data

1. An insurance company evaluates many numerical variables about a person before deciding on an appropriate rate for automobile insurance. The distance a person drives in a year is an example of a variable.

ANSWER:

continuous

TYPE: FI DIFFICULTY: Easy

KEYWORDS: continuous variable, types of data

1. An insurance company evaluates many numerical variables about a person before deciding on an appropriate rate for automobile insurance. A person's age is an example of a numerical variable.

ANSWER:

continuous

TYPE: FI DIFFICULTY: Easy

KEYWORDS: continuous variable, types of data

1. An insurance company evaluates many numerical variables about a person before deciding on an appropriate rate for automobile insurance. How long a person has been a licensed driver is an example of a numerical variable.

ANSWER:

continuous

TYPE: FI DIFFICULTY: Moderate

KEYWORDS: continuous variable, types of data

1. An insurance company evaluates many numerical variables about a person before deciding on an appropriate rate for automobile insurance. The number of tickets a person has received in the last 3 years is an example of a numerical variable.

ANSWER:

discrete

TYPE: FI DIFFICULTY: Easy

KEYWORDS: discrete variable, types of data

1. In purchasing an automobile, there are several variables to consider. The body style of the car (sedan, coupe, wagon, etc.) is an example of a variable.

ANSWER:

categorical

TYPE: FI DIFFICULTY: Easy

KEYWORDS: categorical variable, types of data

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Defining and Collecting Data 1-11

1. In purchasing an automobile, there are several variables to consider. The classification of the car as a subcompact, compact, standard, or luxury size is an example of a variable.

ANSWER:

categorical

TYPE: FI DIFFICULTY: Easy

KEYWORDS: categorical variable, types of data

1. In purchasing an automobile, there are several variables to consider. The color of the car is an example of a variable.

ANSWER:

categorical

TYPE: FI DIFFICULTY: Easy

KEYWORDS: categorical variable, types of data

1. Most colleges admit students based on their achievements in several different areas. Whether a student has taken any advanced placement courses is an example of a variable.

ANSWER:

categorical

TYPE: FI DIFFICULTY: Easy

KEYWORDS: categorical variable, types of data

1. Most colleges admit students based on their achievements in several different areas. The grade obtained in senior level English. (A, B, C, D, or F) is an example of a variable.

ANSWER:

categorical

TYPE: FI DIFFICULTY: Moderate

KEYWORDS: categorical variable, types of data

1. Most colleges admit students based on their achievements in several different areas. The total SAT score achieved by a student is an example of a numerical variable.

ANSWER:

discrete

TYPE: FI DIFFICULTY: Moderate

KEYWORDS: discrete variable, types of data

1. The Dean of Students conducted a survey on campus. The gender of the student is an example of a variable.

ANSWER:

categorical

TYPE: FI DIFFICULTY: Easy

KEYWORDS: categorical variable, types of data

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1-12 Defining and Collecting Data

1. The Dean of Students conducted a survey on campus. Class designation (Freshman, Sophomore, Junior, Senior) is an example of a variable.

ANSWER:

categorical

TYPE: FI DIFFICULTY: Easy

KEYWORDS: categorical variable, types of data

1. The Dean of Students conducted a survey on campus. Major area of study is an example of a

variable.

ANSWER:

categorical

TYPE: FI DIFFICULTY: Easy

KEYWORDS: categorical variable, types of data

1. The Dean of Students conducted a survey on campus. SAT score in mathematics is an example of anumerical variable.

ANSWER:

discrete

TYPE: FI DIFFICULTY: Easy

KEYWORDS: continuous variable, types of data

1. The Dean of Students conducted a survey on campus. Grade point average (GPA) is an example of a numerical variable.

ANSWER:

continuous

TYPE: FI DIFFICULTY: Easy

KEYWORDS: continuous variable, types of data

1. The Dean of Students conducted a survey on campus. Number of credits currently enrolled for is an example of a numerical variable.

ANSWER:

discrete

TYPE: FI DIFFICULTY: Easy

KEYWORDS: discrete variable, types of data

1. The Dean of Students conducted a survey on campus. Number of clubs, groups, teams, and organizations affiliated with on campus is an example of a numerical variable.

ANSWER:

discrete

TYPE: FI DIFFICULTY: Easy

KEYWORDS: discrete variable, types of data

Copyright ©2020 Pearson Education, Inc.

Defining and Collecting Data 1-13

1. A personal computer user survey was conducted. Computer brand primarily used is an example

of a variable.

ANSWER:

categorical

TYPE: FI DIFFICULTY: Easy

KEYWORDS: categorical variable, types of data

1. A personal computer user survey was conducted. Number of personal computers owned is an

example of a numerical variable.

ANSWER:

discrete

TYPE: FI DIFFICULTY: Easy

KEYWORDS: discrete variable, types of data

1. A personal computer user survey was conducted. The number of years using a personal computer is an example of a numerical variable.

ANSWER:

continuous

TYPE: FI DIFFICULTY: Moderate

KEYWORDS: continuous variable, types of data

1. A personal computer user survey was conducted. Hours of personal computer use per week is an example of a numerical variable

ANSWER:

continuous

TYPE: FI DIFFICULTY: Moderate

KEYWORDS: continuous variable, types of data

1. A personal computer user survey was conducted. Primary word processing package used is an example of a variable

ANSWER:

categorical

TYPE: FI DIFFICULTY: Easy

KEYWORDS: categorical variable, types of data

1. A personal computer user survey was conducted. The number of computer magazine subscriptions is an example of a numerical variable.

ANSWER:

discrete

TYPE: FI DIFFICULTY: Moderate

KEYWORDS: discrete variable, types of data

Copyright ©2020 Pearson Education, Inc.

1-14 Defining and Collecting Data

1. The brand of TV one owns is an example of an ordinal scaled variable.

ANSWER:

False

TYPE: TF DIFFICULTY: Easy

KEYWORDS: nominal scale, ordinal scale

1. The brand of TV one owns is an example of a numerical variable.

ANSWER:

False

TYPE: TF DIFFICULTY: Easy

KEYWORDS: categorical variable

1. Whether the university is private, or public is an example of a nominal scaled variable.

ANSWER:

True

TYPE: TF DIFFICULTY: Easy

KEYWORDS: nominal scale

1. Whether the university is private, or public is an example of a categorical variable.

ANSWER:

True

TYPE: TF DIFFICULTY: Easy

KEYWORDS: categorical variable

1. Marital status is an example of an ordinal scaled variable.

ANSWER:

False

TYPE: TF DIFFICULTY: Easy

KEYWORDS: nominal scale, ordinal scale

1. Marital status is an example of a numerical variable.

ANSWER:

False

TYPE: TF DIFFICULTY: Easy

KEYWORDS: categorical variable

1. The grade level (K-12) of a student is an example of a nominal scaled variable.

ANSWER:

True- Nominal scale is used just to identify the grade level as would be as a vehicle identification number. No subjective value is imputed.

TYPE: TF DIFFICULTY: Easy

KEYWORDS: nominal scale, ordinal scale

Copyright ©2020 Pearson Education, Inc.

Defining and Collecting Data 1-15

1. The grade level (K-12) of a student is an example of a numerical variable.

ANSWER:

False

TYPE: TF DIFFICULTY: Easy

KEYWORDS: categorical variable

1. The level of satisfaction (“Very unsatisfied”, “Fairly unsatisfied”, “Fairly satisfied”, and “Very satisfied”) in a class is an example of an ordinal scaled variable.

ANSWER:

True

TYPE: TF DIFFICULTY: Easy

KEYWORDS: ordinal scale

1. The level of satisfaction (“Very unsatisfied”, “Fairly unsatisfied”, “Fairly satisfied”, and “Very satisfied”) in a class is an example of a categorical variable.

ANSWER:

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