Chapter 01
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WebQuizzing – Ch.01
Book ISBN-10 0538477490
Book ISBN-13 9780538477499
Author: Gerald Keller
Title: Statistics for Management and Economics
Ed: 9e
# Questions Submitted: 20 Multiple Choice
1. You take a random sample of 100 students at your university and find that their average GPA
is 3.1. If you use this information to help you estimate the average GPA for all students at
your university, then you are doing what branch of statistics?
a. Descriptive statistics
b. Inferential statistics
c. Sample statistics
d. Population statistics
Analysis:
A. Incorrect. This is Inferential Statistics.
B. Correct. This is Inferential Statistics.
C. Incorrect. This is Inferential Statistics.
D. Incorrect This is Inferential Statistics.
ANSWER: B Ref: Section 1.1
2. A company has developed a new computer sound card whose average lifetime is unknown.
In order to estimate this average, 200 sound cards are randomly selected from a large
production line and tested; their average lifetime is found to be 5 years. The 200 sound cards
represent a:
a. parameter.
b. statistic.
c. sample.
d. population.
Analysis:
A. Incorrect This represents a sample.
B. Incorrect This represents a sample.
C. Correct. This represents a sample.
D. Incorrect This represents a sample.
ANSWER: C Ref: Section 1.1
3. A descriptive measure that is computed from a sample is called a:
a. parameter.
b. statistic.
c. population.
d. sample.
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Analysis:
A. Incorrect A descriptive measure that is computed from a sample is called a statistic.
B. Correct A descriptive measure that is computed from a sample is called a statistic.
C. Incorrect A descriptive measure that is computed from a sample is called a statistic.
D. Incorrect A descriptive measure that is computed from a sample is called a statistic.
ANSWER: b
Ref: Section 1.1
4. A summary measure that is computed from a population is called a:
A. sample.
B. statistic.
C. population.
D. parameter.
Analysis:
A. Incorrect A summary measure that is computed from a population is called a parameter.
B. Incorrect A summary measure that is computed from a population is called a parameter.
C. Incorrect. A summary measure that is computed from a population is called a parameter.
D. Correct. A summary measure that is computed from a population is called a parameter.
ANSWER: D Ref: Section 1.1
5. Which of the following is a measure of the reliability of a statistical inference?
A. A population parameter.
B. A significance level.
C. A descriptive statistic.
D. A sample statistic.
Analysis:
A. Incorrect. A significance level is the measure of the reliability of a statistical inference.
B. Correct. A significance level is the measure of the reliability of a statistical inference.
C. Incorrect. A significance level is the measure of the reliability of a statistical inference.
D. Incorrect. A significance level is the measure of the reliability of a statistical inference.
ANSWER: B Ref: Section 1.1
6. A politician who is running for the office of governor of a state with 4 million registered
voters commissions a survey. In the survey, 54% of the 5,000 registered voters interviewed
say they plan to vote for her. The population of interest is:
A. the 4 million registered voters in the state.
B. the 5,000 registered voters interviewed.
C. the 54% who plan to vote for her.
D. all the residents of the state.
Analysis:
A. Correct. The population of interest is the total number of voters.
B. Incorrect. The population of interest is the total number of voters.
C. Incorrect. The population of interest is the total number of voters.
D. Incorrect. The population of interest is the total number of voters.
ANSWER: A Ref: Section 1.1
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7. The process of using sample statistics to draw conclusions about population parameters is
called:
A. finding the significance level.
B. calculating descriptive statistics.
C. doing inferential statistics.
D. calculating the confidence level.
Analysis:
A. Incorrect. The process of using sample statistics to draw conclusions about population
parameters is called doing inferential statistics.
B. Incorrect. The process of using sample statistics to draw conclusions about population
parameters is called doing inferential statistics.
C. Correct. The process of using sample statistics to draw conclusions about population
parameters is called doing inferential statistics .
D. Incorrect. The process of using sample statistics to draw conclusions about population
parameters is called doing inferential statistics.
ANSWER:C Ref: Section 1.1
8. How do confidence levels compare to significance levels?
A. Confidence levels and significance levels are both typically small.
B. Confidence levels and significance levels are both typically large.
C. Confidence levels are typically small and significance levels are typically large.
D. Confidence levels are typically large and significance levels are typically small.
Analysis:
A. Incorrect. Confidence levels are typically large and significance levels are typically small.
B. Incorrect. Confidence levels are typically large and significance levels are typically small.
C. Incorrect. Confidence levels are typically large and significance levels are typically small.
D. Correct. Confidence levels are typically large and significance levels are typically small.
ANSWER: d Ref: Section 1.1
9. The significance level of a statistical inference measures:
A. the proportion of times a conclusion about a population will be correct in the long run.
B. the proportion of times a conclusion about a population will be wrong in the long run.
C. the proportion of times an estimation procedure will be correct in the long run.
D. the proportion of times an estimation procedure will be wrong in the long run.
Analysis:
A. Incorrect. The significance level of a statistical inference measures the proportion of times a
conclusion about a population will be wrong in the long run.
B. Correct. The significance level of a statistical inference measures the proportion of times a
conclusion about a population will be wrong in the long run.
C. Incorrect. The significance level of a statistical inference measures the proportion of times a
conclusion about a population will be wrong in the long run.
D. Incorrect. The significance level of a statistical inference measures the proportion of times a
conclusion about a population will be wrong in the long run.
ANSWER: B Ref: Section 1.1
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10. The confidence level of a statistical inference measures:
A. the proportion of times a conclusion about a population will be correct in the long run.
B. the proportion of times a conclusion about a population will be wrong in the long run.
C. the proportion of times an estimation procedure will be correct in the long run.
D. the proportion of times an estimation procedure will be wrong in the long run.
Analysis:
A. Incorrect. The confidence level of a statistical inference measures the proportion of times an
estimation procedure will be correct in the long run.
B. Incorrect. The confidence level of a statistical inference measures the proportion of times an
estimation procedure will be correct in the long run.
C. Correct. The confidence level of a statistical inference measures the proportion of times an
estimation procedure will be correct in the long run.
D. Incorrect. The confidence level of a statistical inference measures the proportion of times an
estimation procedure will be correct in the long run.
ANSWER: C Ref: Section 1.1
11. At Grand Rapids Community College, administrators want to determine the average
commuting distance for their students who commute to school. They randomly select 150
students who commute and ask them the distance of their commute to campus. From this
group a mean of 18.2 miles is computed. The parameter in this example is:
A. The mean commute distance for all commuting students at the college.
B. 18.2 miles.
C. All commuting students enrolled at the college.
D. The 150 randomly selected commuting students.
Analysis:
A. Correct. The parameter in this example is the mean commute distance for all commuting
students at the college.
B. Incorrect. The parameter in this example is the mean commute distance for all commuting
students at the college.
C. Incorrect. The parameter in this example is the mean commute distance for all commuting
students at the college.
D. Incorrect. The parameter in this example is the mean commute distance for all commuting
students at the college.
ANSWER: A Ref: Section 1.1
12. At Miami Dade Community College, administrators want to determine the average
commuting distance for their students who commute to school. They randomly select 300
students who commute and ask them the distance of their commute to campus. From this
group a mean of 15.4 miles is computed. Find the statistic in this example.
A. The 300 randomly selected commuting students.
B. 15.4 miles.
C. The mean commute distance for all commuting students at the college.
D. All commuting students enrolled at the college.
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Analysis:
A. Incorrect. The statistic from this group is the computed mean of 15.4 miles.
B. Correct. The statistic from this group is the computed mean of 15.4 miles.
C. Incorrect. The statistic from this group is the computed mean of 15.4 miles.
D. Incorrect. The statistic from this group is the computed mean of 15.4 miles.
ANSWER: B Ref: Section 1.1
13. At Vassar College, administrators want to determine the average commuting distance for
their students who commute to school. They randomly select 250 students who commute and
ask them the distance of their commute to campus. From this group a mean of 21.3 miles is
computed. What is the population in this example?
A. 21.3 miles
B. The mean commute distance for all commuting students at the college..
C. All commuting students enrolled at the college.
D. The 250 randomly selected commuting students
Analysis:
A. Incorrect. The population in this example is the total of all commuting students.
B. Incorrect. The population in this example is the total of all commuting students.
C. Correct. The population in this example is the total of all commuting students.
D. Incorrect. The population in this example is the total of all commuting students.
ANSWER: C Ref: Section 1.1
14. What is the sample in the following example? The administrators at West Virginia University
want to determine the average commuting distance for their students who commute to school.
They randomly select 450 students who commute and ask them the distance of their
commute to campus. From this group a mean of 24.3 miles is computed
A.
B.
C.
D.
All commuting students enrolled at the college.
The mean commute distance for all commuting students at the university.
24.3 miles.
The 450 randomly selected commuting students.
Analysis:
A. Incorrect. The sample is the 450 randomly selected commuting students.
B. Incorrect. The sample is the 450 randomly selected commuting students.
C. Incorrect. The sample is the 450 randomly selected commuting students.
D. Correct. The sample is the 450 randomly selected commuting students.
ANSWER: D Ref: Section 1.1
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15. Descriptive statistics is the:
A. organizing, summarizing, and analyzing data to describe a sample.
B. process of making an estimate, prediction, or decision about a population based on
sample data.
C. proportion of times that an estimating procedure will be correct in the long run.
D. proportion of times that a conclusion about a population will be wrong in the long run.
Analysis:
A. Correct. Descriptive statistics is the organizing, summarizing, and analyzing data to describe
a sample.
B. Incorrect. Descriptive statistics is the organizing, summarizing, and analyzing data to
describe a sample.
C. Incorrect. Descriptive statistics is the organizing, summarizing, and analyzing data to
describe a sample.
D. Incorrect. Descriptive statistics is the organizing, summarizing, and analyzing data to
describe a sample.
ANSWER: A Ref: Section 1.1
16. Statistical inference is the:
A. organizing, summarizing, and analyzing data to describe a sample.
B. process of making an estimate, prediction, or decision about a population based on
sample data.
C. proportion of times that an estimating procedure will be correct in the long run.
D. proportion of times that a conclusion about a population will be wrong in the long run.
Analysis:
A. Incorrect. Statistical inference is the process of making an estimate, prediction, or decision
about a population based on sample data.
B. Correct. Statistical inference is the process of making an estimate, prediction, or decision
about a population based on sample data.
C. Incorrect. Statistical inference is the process of making an estimate, prediction, or decision
about a population based on sample data.
D. Incorrect. Statistical inference is the process of making an estimate, prediction, or decision
about a population based on sample data.
ANSWER: B Ref: Section 1.1
17. The confidence level is the:
A. organizing, summarizing, and analyzing data to describe a sample.
B. process of making an estimate, prediction, or decision about a population based on
sample data.
C. proportion of times that an estimating procedure will be correct in the long run.
D. proportion of times that a conclusion about a population will be wrong in the long run.
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Analysis:
A. Incorrect. The confidence level is the proportion of times that an estimating procedure will be
correct in the long run.
B. Incorrect. The confidence level is the proportion of times that an estimating procedure will be
correct in the long run.
C. Correct. The confidence level is the proportion of times that an estimating procedure will be
correct in the long run.
D. Incorrect. The confidence level is the proportion of times that an estimating procedure will be
correct in the long run.
ANSWER: C Ref: Section 1.1
18. A population is the:
A. proportion of times that an estimating procedure will be correct in the long run.
B. proportion of times that a conclusion about a population will be wrong in the long run.
C. group of all items of interest to a statistics practitioner.
D. set of data drawn from the population.
Analysis:
A. Incorrect. A population is the group of all items of interest to a statistics practitioner.
B. Incorrect. A population is the group of all items of interest to a statistics practitioner.
C. Correct. A population is the group of all items of interest to a statistics practitioner.
D. Incorrect. A population is the group of all items of interest to a statistics practitioner.
ANSWER: C Ref: Section 1.1
19. A sample is a:
A. proportion of times that an estimating procedure will be correct in the long run.
B. proportion of times that a conclusion about a population will be wrong in the long run.
C. group of all items of interest to a statistics practitioner.
D. set of data drawn from the population.
Analysis:
A. Incorrect. A sample is a set of data drawn from the population.
B. Incorrect. A sample is a set of data drawn from the population.
C. Incorrect. A sample is a set of data drawn from the population.
D. Correct. A sample is a set of data drawn from the population.
ANSWER: D Ref: Section 1.1
20. Which of the following represents a population, as opposed to a sample?
A. 2,000 respondents to a magazine survey which has 100,000 subscribers.
B. All registered voters in the state of North Dakota.
C. The first 20 students in your class completing a final exam.
D. Every third student to arrive at the gym on your campus.
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Analysis:
A. Incorrect. A population is the group of all items of interest to a statistics practitioner.
B. Correct. A population is the group of all items of interest to a statistics practitioner.
C. Incorrect. A population is the group of all items of interest to a statistics practitioner.
D. Incorrect. A population is the group of all items of interest to a statistics practitioner.
ANSWER: B Ref: Section 1.1