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Business Statistics for Contemporary Decision Making 7th Edition Test Bank | Complete Questions and Answers | Statistics Exam Prep Guide

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Achieve success in business statistics with this comprehensive Business Statistics for Contemporary Decision Making 7th Edition Test Bank. Designed for business, management, economics, finance, and data analytics students, this study resource provides chapter-by-chapter practice questions and answers to help master statistical concepts and improve exam performance.

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File: ch01, Chapter 1: Introduction to Statistics

,True/False



1. Virtually all areas of business use statistics in decision making.

Ans: True
Response: See section 1.1, Statistics in Business
Difficulty: Easy
Learning Objective: 1.1: List quantitative and graphical examples of statistics within a business
context.



2. The complete collection of all entities under study is called the sample.

Ans: False
Response: See section 1.2, Basic Statistical Concepts
Difficulty: Easy
Learning Objective: 1.2: define important statistical terms, including population, sample, and
parameter, as they relate to descriptive and inferential statistics.



3. A portion or subset of the entities under study is called the statistic.

Ans: False
Response: See section 1.2, Basic Statistical Concepts
Difficulty: Easy
Learning Objective: 1.2: define important statistical terms, including population, sample, and
parameter, as they relate to descriptive and inferential statistics.



4. A descriptive measure of the population is called a parameter.

Ans: True
Response: See section 1.2, Basic Statistical Concepts
Difficulty: Easy
Learning Objective: 1.2: define important statistical terms, including population, sample, and
parameter, as they relate to descriptive and inferential statistics.

,5. A census is the process of gathering data on all the entities in the population.

Ans: True
Response: See section 1.2, Basic Statistical Concepts
Difficulty: Easy
Learning Objective: 1.2: define important statistical terms, including population, sample, and
parameter, as they relate to descriptive and inferential statistics.



6. Statistics is commonly divided into two branches called descriptive statistics and summary
statistics.

Ans: False
Response: See section 1.2, Basic Statistical Concepts
Difficulty: Easy
Learning Objective: 1.2: define important statistical terms, including population, sample, and
parameter, as they relate to descriptive and inferential statistics.




7. A descriptive measure of the sample is called a statistic.

Ans: True
Response: See section 1.2, Basic Statistical Concepts
Difficulty: Easy
Learning Objective: 1.2: define important statistical terms, including population, sample, and
parameter, as they relate to descriptive and inferential statistics.



8. Gathering data from a sample to reach conclusions about the population from which the
sample was drawn is called descriptive statistics.

Ans: False
Response: See section 1.2, Basic Statistical Concepts
Difficulty: Medium
Learning Objective: 1.2: define important statistical terms, including population, sample, and
parameter, as they relate to descriptive and inferential statistics.

, 9. Calculation of population parameters is usually either impossible or excessively time
consuming and costly.

Ans: True
Response: See section 1.2, Basic Statistical Concepts
Difficulty: Easy
Learning Objective: 1.2: define important statistical terms, including population, sample, and
parameter, as they relate to descriptive and inferential statistics.



10. The basis for inferential statistics is the ability to make decisions about population parameters
without having to complete a census of the population.

Ans: True
Response: See section 1.2, Basic Statistical Concepts
Difficulty: Easy
Learning Objective: 1.2: define important statistical terms, including population, sample, and
parameter, as they relate to descriptive and inferential statistics.




11. All numerical data must be analyzed statistically in the same way because all of them are
represented by numbers.

Ans: False
Response: See section 1.4, Data Measurement
Difficulty: Medium
Learning Objective: 1.4: Compare the four different levels of data: nominal, ordinal, interval, and
ratio.




12. The manner in which numerical data can be analyzed statistically depends on the level of data
measurement represented by numbers being analyzed.

Ans: True
Response: See section 1.4, Data Measurement
Difficulty: Medium
Learning Objective: 1.4: Compare the four different levels of data: nominal, ordinal, interval, and
ratio.

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