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Exam (elaborations)

Business Statistics for Contemporary Decision Making: Exam Preparation Guide (Chapters 1-6)

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This resource contains a comprehensive set of true/false and multiple-choice questions from Chapters 1 to 6 of Business Statistics for Contemporary Decision Making, 7th Edition by Ken Black. It covers foundational topics such as introduction to statistics, data measurement, charts and graphs, descriptive statistics, probability, discrete distributions, and continuous distributions. Ideal for students and instructors seeking practice questions to reinforce understanding of statistical concepts applied in business contexts.

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Institution
Business Statistics For Contemporary Decision Maki
Course
Business Statistics for Contemporary Decision Maki

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,File: ch01, Chapter 1: Introduction to Statistics
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True/False



1. Virtually all areas of business use statistics in decision making.
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Ans: True
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Response: See section 1.1, Statistics in Business
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Difficulty: Easy
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Learning Objective: 1.1: List quantitative and graphical examples of statistics within a business
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context.



2. The complete collection of all entities under study is called the sample.
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Ans: False
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Response: See section 1.2, Basic Statistical Concepts
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Difficulty: Easy
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Learning Objective: 1.2: define important statistical terms, including population, sample, and
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parameter, as they relate to descriptive and inferential statistics.
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3. A portion or subset of the entities under study is called the statistic.
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Ans: False
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Response: See section 1.2, Basic Statistical Concepts
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Difficulty: Easy
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Learning Objective: 1.2: define important statistical terms, including population, sample, and
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parameter, as they relate to descriptive and inferential statistics.
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4. A descriptive measure of the population is called a parameter.
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Ans: True
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Response: See section 1.2, Basic Statistical Concepts
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Difficulty: Easy
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Learning Objective: 1.2: define important statistical terms, including population, sample, and
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parameter, as they relate to descriptive and inferential statistics.
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,5. A census is the process of gathering data on all the entities in the population.
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Ans: True
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Response: See section 1.2, Basic Statistical Concepts
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Difficulty: Easy
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Learning Objective: 1.2: define important statistical terms, including population, sample, and
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parameter, as they relate to descriptive and inferential statistics.
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6. Statistics is commonly divided into two branches called descriptive statistics and summary
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statistics.
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Ans: False
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Response: See section 1.2, Basic Statistical Concepts
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Difficulty: Easy
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Learning Objective: 1.2: define important statistical terms, including population, sample, and
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parameter, as they relate to descriptive and inferential statistics.
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7. A descriptive measure of the sample is called a statistic.
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Ans: True
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Response: See section 1.2, Basic Statistical Concepts
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Difficulty: Easy
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Learning Objective: 1.2: define important statistical terms, including population, sample, and
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parameter, as they relate to descriptive and inferential statistics.
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8. Gathering data from a sample to reach conclusions about the population from which the
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sample was drawn is called descriptive statistics.
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Ans: False
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Response: See section 1.2, Basic Statistical Concepts
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Difficulty: Medium
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Learning Objective: 1.2: define important statistical terms, including population, sample, and
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parameter, as they relate to descriptive and inferential statistics.
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, 9. Calculation of population parameters is usually either impossible or excessively time
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consuming and costly.
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Ans: True
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Response: See section 1.2, Basic Statistical Concepts
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Difficulty: Easy
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Learning Objective: 1.2: define important statistical terms, including population, sample, and
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parameter, as they relate to descriptive and inferential statistics.
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10. The basis for inferential statistics is the ability to make decisions about population parameters
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without having to complete a census of the population.
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Ans: True
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Response: See section 1.2, Basic Statistical Concepts
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Difficulty: Easy
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Learning Objective: 1.2: define important statistical terms, including population, sample, and
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parameter, as they relate to descriptive and inferential statistics.
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11. All numerical data must be analyzed statistically in the same way because all of them are
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represented by numbers.
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Ans: False
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Response: See section 1.4, Data Measurement
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Difficulty: Medium
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Learning Objective: 1.4: Compare the four different levels of data: nominal, ordinal, interval, and
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ratio.



12. The manner in which numerical data can be analyzed statistically depends on the level of data
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measurement represented by numbers being analyzed.
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Ans: True
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Response: See section 1.4, Data Measurement
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Difficulty: Medium
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Learning Objective: 1.4: Compare the four different levels of data: nominal, ordinal, interval, and
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ratio.

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Institution
Business Statistics for Contemporary Decision Maki
Course
Business Statistics for Contemporary Decision Maki

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Uploaded on
September 20, 2025
Number of pages
615
Written in
2025/2026
Type
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