## Business Statistics in Practice 3rd Canadian Edition By Bruce – Test Bank

The Business Statistics in Practice 3rd Canadian Edition Test Bank, authored by Bruce L. Bowerman, Richard T. O’Connell, and Emilly S. Murphree, is a comprehensive resource designed to help students understand the fundamental concepts of business statistics. The test bank is an invaluable tool for instructors, as it contains a wide range of multiple-choice questions, true/false statements, and short answer questions that are perfect for use in exams, quizzes, and assignments.

The Business Statistics in Practice test bank covers a wide range of topics, including data analysis, probability, sampling, hypothesis testing, regression analysis, and more. Each chapter contains a wealth of questions and problems that are designed to help students gain a deep understanding of the concepts covered in the textbook.

One of the key features of the Business Statistics in Practice test bank is the emphasis on real-world applications. The questions and problems are designed to simulate real-world scenarios that students are likely to encounter in the workplace. This approach helps to prepare students for the challenges of the modern business world and helps them to apply their statistical knowledge in practical ways.

In addition to the traditional test bank questions, the Business Statistics in Practice test bank also includes Excel exercises that allow students to practice their statistical analysis skills using the popular spreadsheet software. This is an excellent way to help students develop their practical skills and gain hands-on experience with statistical analysis.

Overall, the Business Statistics in Practice 3rd Canadian Edition Test Bank is an excellent resource for students and instructors alike. It provides a comprehensive set of questions and problems that are perfect for use in exams, quizzes, and assignments, and it is an invaluable tool for anyone who wants to gain a deeper understanding of business statistics.

**Chapter 1 Content **

*Student: ___________________________________________________________________________*

1. A population is a set of units (usually people, objects, or events).

True False

2. If we examine half of the population measurements, we are conducting a census of the population.

True False

3. A random sample is selected so that, on each selection from the population, every unit remaining in the population on that selection has the same chance of being chosen.

True False

4. A process is in statistical control if it does not exhibit any unusual process variations.

True False

5. An example of a quantitative variable is the make of a car.

True False

6. An example of a qualitative variable is the fuel efficiency of a car, measured in L/100km.

True False

7. Statistical inference is the science of using a sample of measurements to make generalizations about the important aspects of a population of measurements.

True False

8. If we sample without replacement, we do not place the unit chosen on a particular selection back into the population.

True False

9. By taking a systematic sample, in which we select every 100^{th} shopper arriving at a specific store, we are approximating a random sample of shoppers.

True False

10. Nonresponse reduces the sample size and may have a negative impact on the generalization of results if the individuals who do not respond are themselves nonrandom.

True False

11. Undercoverage is when some units of the population are mistakenly included in the sample.

True False

12. Suppose that the six students listed belearning Objective: w have applied for a bursary.

1. Justin 2. Gordon 3. Ahmed 4. Melanie 5. Olga 6. Ian

Only three students can receive the bursary. Because they have all met the criteria for the bursary, the three students who will receive the bursary will be selected at random. Consider the follearning Objective: wing list of random digits from a random number table:

27102 56027 55892 33063 41842 81868 71035 09001 43367 49497 54580 81507

Starting with the leftmost digit, use this list of random digits to choose a simple random sample of three students from the six students listed above. The sample you obtain is

A. Olga, Ian, and Ahmed.

B. Melanie, Ahmed, and Ian.

C. Justin, Gordon, and Olga.

D. Justin, Gordon, and Gordon again.

E. any set of 3 names, but we must exclude Gordon.

13. Ratio variables have the follearning Objective: wing unique characteristic:

A. Meaningful order

B. An arbitrarily defined zero value

C. Categorical in nature

D. Predictable with 100% accuracy

E. Equal distance between points

14. When we are choosing a random sample and we do not place chosen units back into the population, we are

A. sampling with replacement.

B. sampling by convenience.

C. using a systematic sample.

D. using a voluntary response sample.

E. sampling without replacement.

15. Which one of the follearning Objective: wing is a quantitative variable?

A. The make of a TV.

B. A person’s gender.

C. A person’s height.

D. Whether a person is an university graduate or not.

E. Whether a person has a credit card.

16. Which one of the follearning Objective: wing is a categorical variable?

A. Air temperature.

B. Bank account balance.

C. Daily sales in a store.

D. Whether a person has a traffic violation.

E. Value of company stock.

17. Measurements from a population are also known as

A. statistics.

B. observations.

C. variables.

D. processes.

E. functions.

18. If the runs plearning Objective: t for a process shows increasing variation around a constant level, then the process is

A. reliable.

B. capable.

C. profitable.

D. predictable.

E. out of control.

19. The two levels of measurement for quantitative variables are

A. ordinal and ratio.

B. interval and ordinal.

C. nominative and ordinal.

D. interval and ratio.

E. nominative and interval.

20. Temperature, (in degrees Celsius) is an example of a(n) ________ variable.

A. nominative

B. ordinal

C. interval

D. ratio

E. random

21. Jersey numbers of soccer players are an example of a(n) ___________ variable.

A. nominative

B. ordinal

C. interval

D. ratio

E. random

22. Weights of items obtained using a well-adjusted scale represents a(n) _____________ level of measurement.

A. nominative

B. ordinal

C. interval

D. ratio

E. balanced

23. An identification of police officers by rank would represent a(n) ____________ level of measurement.

A. nominative

B. ordinal

C. interval

D. ratio

E. professional

24. __________ is a necessary component of a runs plearning Objective: t.

A. Observation over time

B. A qualitative variable

C. Random sampling of the data

D. Voluntary response data

E. A Likert scale survey

25. ______________ is the science of using a sample of measurements to make generalizations about the important aspects of a population.

A. Statistical process control

B. Descriptive statistics

C. Random sample

D. Statistical inference

E. Deductive reasoning

26. Degree program entrance exam scores, such as MCAT scores, are an example of a(n) ________________ variable.

A. ordinal

B. ratio

C. nominative

D. interval

E. undefined

27. The number of kilearning Objective: metres a truck is driven before it is overhauled is an example of a(n) _____________ variable.

A. nominative

B. ordinal

C. interval

D. ratio

E. maintenance

28. Which one of the following sampling methods would generally lead to the least reliable statistical inferences about the population from which the sample has been selected?

A. A random sample selected without replacement.

B. A random sample selected with replacement.

C. A voluntary response sample.

D. A systematic sample.

E. A stratified random sample.

29. A(n) _____ variable is a qualitative variable such that there is no meaningful ordering or ranking of the categories.

A. ratio

B. ordinal

C. nominative

D. interval

E. random

30. A person’s telephone area code is an example of a(n) _____________ variable.

A. nominative

B. ordinal

C. interval

D. ratio

E. independent

31. Any characteristic of a population unit is a(n):

A. measurement

B. sample

C. observation

D. variable

E. trait

32. A list of all of the units in a population is called a _____.

A. census

B. frame

C. random sample

D. variable

E. systematic sample

33. The two levels of measurement for qualitative variables are

A. ordinal and ratio.

B. interval and ordinal.

C. nominative and ordinal.

D. interval and ratio.

E. nominative and interval.

34. Each customer in a market research study is asked to identify their favourite beverage. The level of measurement for this study would be at the _____ level.

A. nominal

B. ordinal

C. interval

D. ratio

E. quantitative

35. In sampling from the population, a _____ is a unique group representing a segment of the population of interest and which has been predetermined by the researcher.

A. focus group

B. system

C. parliament

D. response

E. stratum

36. When a researcher uses a(n) _____ sample, they decrease bias in the sample.

A. voluntary response

B. small

C. expensive

D. random

E. convenience

37. A researcher believes a person’s gender will influence their answer to a particular question. In order to take this into account, the researcher selects a random sample of 100 men and another random sample of 100 women. This is an example of a ______ sample.

A. stratified random

B. simple random

C. biased

D. multistage cluster

E. systematic

38. A _____ plot is a graph of individual process measurements versus time.

A. line

B. runs

C. scatter

D. pie-chart

E. stem

39. A machine produces pencils. At the start of the day, the potential number of pencils produced is _____. At the end of the day, the actual number of pencils produced is _____.

A. finite, infinite

B. actual, probable

C. infinite, finite

D. staged, actual

E. controlled, measured

40. If a process does not exhibit any unusual process variations, then the process is said to be in _________.

________________________________________

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