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Test Bank — Basic Business Statistics, 15th Edition — by Mark L. Berenson, David M. Levine, David F. Stephan

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The Test Bank for Basic Business Statistics, 15th Edition by Berenson, Levine, and Stephan offers a complete and reliable set of exam-ready questions designed to support teaching and learning in business statistics courses. Covering a wide range of fundamental and advanced topics, the test bank aligns directly with the chapters of the textbook. These include: Defining and Collecting Data; Tabular and Visual Summarization of Variables; Numerical Descriptive Measures; Basic Probability; Discrete Probability Distributions; The Normal Distribution and Other Continuous Distributions; Sampling Distributions; Confidence Interval Estimation; Fundamentals of Hypothesis Testing: One-Sample Tests; Two-Sample Tests; Analysis of Variance; Chi-Square and Nonparametric Tests; Simple Linear Regression; Introduction to Multiple Regression; More Complex Multiple Regression Models; Time-Series Forecasting; Business Analytics; Getting Ready to Analyze Data in the Future; Statistical Applications in Quality Management (Online); and Decision Making (Online). Each chapter features multiple-choice questions, conceptual items, calculation-based problems, and scenario-driven applications. This resource is ideal for instructors and educators developing quizzes, assignments, midterms, and final exams in undergraduate and MBA-level statistics and data analytics courses.

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Basic Business Statistics – 15th

Edition
ST
UV

TEST BANK
IA
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Mark L. Berenson
AP

David M. Levine
PR

David F. Stephan
OV

Comprehensive Test Bank for Instructors

and Students
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© Mark L. Berenson, David M. Levine & David F. Stephan
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All rights reserved. Reproduction or distribution without permission is prohibited.



Created by MedConnoisseur ©2025/2026

, TABLE OF CONTENTS
Basic Business Statistics – 15th Edition
ST

Mark L. Berenson, David M. Levine & David F. Stephan
UV

1. Defining and Collecting Data
2. Tabular and Visual Summarization of Variables
3. Numerical Descriptive Measures
4. Basic Probability
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5. Discrete Probability Distributions
6. The Normal Distribution and Other Continuous Distributions
7. Sampling Distributions
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8. Confidence Interval Estimation
9. Fundamentals of Hypothesis Testing: One-Sample Tests
10.Two-Sample Tests
11.Analysis of Variance
AP

12.Chi-Square and Nonparametric Tests
13.Simple Linear Regression
14.Introduction to Multiple Regression
15.More Complex Multiple Regression Models
PR
16.Time-Series Forecasting
17.Business Analytics
18.Getting Ready to Analyze Data in the Future
19.Statistical Applications in Quality Management (Online)
OV
20.Decision Making (Online)
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Created by MedConnoisseur ©2025/2026

, Test Bank For Basic Business Statistics, 15th Edition by Mark L. Berenson David M. Levine David F. Stephan
Exam

Name
ST
MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question.

1) The process of using data collected from a small group to reach conclusions about a large group is called
A) DCOVA framework. B) descriptive statistics.
C) statistical inference. D) operational definition.
UV
2) 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) DCOVA framework. B) statistical inference.
C) descriptive statistics. D) operational definition.
IA
3) 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) DCOVA framework.
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C) operational definition. D) descriptive statistics.



4) The estimation of the population average family expenditure on food based on the sample average expenditure of
1,000 families is an example of
AP
A) inferential statistics. B) DCOVA framework.
C) operational definition. D) descriptive statistics.



5) Which of the following is not an element of descriptive statistical problems?
PR
A) Tables, graphs, or numerical summary tools.
B) An inference made about the population based on the sample.
C) Identification of patterns in the data.
D) The population or sample of interest.
OV
6) 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.
A) True
B) False
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7) 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.
A) True
B) False
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, 8) 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.
A) True
B) False
ST
9) 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.
A) True
B) False
UV
10) 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.
A) True
B) False
IA
SHORT ANSWER. Write the word or phrase that best completes each statement or answers the question.

11) The Human Resources Director of a large corporation wishes to develop an employee benefits package and
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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 .
AP
12) 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 .
PR
13) 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
OV
characteristics based on information obtained from the sample is called .



14) 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
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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 .
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2

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