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<< Business A Practical Introduction 1st Edition by Williams Test Bank | Business Law Alternate Edition Text and Summarized Cases 12th Edition by Roger LeRoy Miller Frank B. Cross Test Bank >> |

CHAPTER 1: WHAT IS STATISTICS?

TRUE/FALSE

1. The significance level measures the proportion of the time an inference about a population will be correct in the long run.

ANS: F NAT: Analytic; Statistical Inference

2. A summary measure that is computed from a sample is called a statistic.

ANS: T NAT: Analytic; Statistical Inference

3. The confidence level is the proportion of times that an estimating procedure will be wrong in the long run.

ANS: F NAT: Analytic; Statistical Inference

4. A resort employs 3,500 managers and staff. To ascertain their employees opinions of a proposed health insurance plan, 350 employees are surveyed at random. The proportion of the 350 employees who favor the health insurance plan represents a parameter in this scenario.

ANS: F NAT: Analytic; Statistical Inference

5. In a sample of 350 students selected from a large college of business, 25% are found to be marketing majors. The 25% is a statistic.

ANS: T NAT: Analytic; Statistical Inference

6. 35% of a sample of 300 professional baseball players indicated that their parents did not play baseball. Based on this sample, we estimate that approximately 35% of the parents of all professional baseball players did not play baseball, plus or minus 5%. This is an example of using inferential statistics.

ANS: T NAT: Analytic; Statistical Inference

7. A population is the group of all items of interest to a statistics practitioner.

ANS: T NAT: Analytic; Statistical Inference

8. A statistic is typically a known quantity while a parameter is typically an unknown quantity.

ANS: T NAT: Analytic; Statistical Inference

9. Statistical inference is the process of making an estimate, prediction, or decision about a population based on sample data.

ANS: T NAT: Analytic; Statistical Inference

10. A descriptive measure of a population is called a parameter.

ANS: T NAT: Analytic; Statistical Inference

11. A descriptive measure of a sample is called a parameter.

ANS: F NAT: Analytic; Statistical Inference

12. You take a random sample to estimate a population mean and your results have a confidence level of 80%. That means the process you used will give you correct results 80% of the time.

ANS: T NAT: Analytic; Statistical Inference

MULTIPLE CHOICE

13. A random sample of 100 students is taken at LearnAll University and its found that their average GPA is 3.1. If this information is used to help estimate the average GPA for all students at LearnAll University, which branch of statistics was applied?

a. Descriptive statistics

b. Inferential statistics

c. Sample statistics

d. Population statistics

ANS: B NAT: Analytic; Statistical Inference

14. A company has developed a new computer microprocessor whose average lifetime is unknown. In order to estimate this average, 300 microprocessors are randomly selected from a large production line and tested; their average lifetime is found to be 7 years. The 300 microprocessors represent a:

a. parameter.

b. statistic.

c. sample.

d. population.

ANS: C NAT: Analytic; Statistical Inference

15. A company has developed a new engine whose average lifetime is unknown. In order to estimate this average, 100 engines are randomly selected from a large production line and tested; their average lifetime is found to be 11 years. The 11 years represents a:

a. parameter.

b. statistic.

c. sample.

d. population.

ANS: B NAT: Analytic; Statistical Inference

16. A descriptive measure that is computed from a sample is called a:

a. parameter.

b. statistic.

c. population.

d. sample.

ANS: B NAT: Analytic; Statistical Inference

17. A summary measure that is computed from a population is called a:

a. sample.

b. statistic.

c. population.

d. parameter.

ANS: D NAT: Analytic; Statistical Inference

18. 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.

ANS: B NAT: Analytic; Statistical Inference

19. A councilman who is running for the office of senator of a state with 3.5 million registered voters commissions a survey. In the survey, 46% of the 8,000 registered voters interviewed say they plan to vote for him. The population of interest is:

a. the 3.5 million registered voters in the state.

b. the 8,000 registered voters interviewed.

c. the 46% who plan to vote for her.

d. all the residents of the state.

ANS: A NAT: Analytic; Statistical Inference

20. A company has developed a new power cell and wants to estimate its average lifetime. A random sample of 650 power cells is tested and the average lifetime of this sample is found to be 315 hours. The 315 hours is the value of a:

a. parameter.

b. statistic.

c. sample.

d. population.

ANS: B NAT: Analytic; Statistical Inference

21. 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.

ANS: C NAT: Analytic; Statistical Inference

22. Which of the following represents a population, as opposed to a sample?

a. 2,000 respondents to a magazine survey which has 600,000 subscribers.

b. The first 15 students in your class completing a final exam.

c. Every fourth student to arrive at the book store on your campus.

d. All registered voters in the state of West Virginia

ANS: D NAT: Analytic; Statistical Inference

23. A researcher at Florida International University (FIU) wants to estimate the average number of credits earned by students last semester at FIU. She randomly selects 750 students from last semester and finds that they averaged 13.75 credits per student. The population of interest to the researcher is:

a. all FIU students.

b. all college students.

c. all FIU students enrolled last semester.

d. the 750 FIU students selected at random.

ANS: C NAT: Analytic; Statistical Inference

24. A study is under way to determine the average height of all 63,000 adult walnut trees in a certain national forest. The heights of 950 randomly selected adult walnut trees are measured and analyzed. The sample in this study is:

a. the average height of the 950 randomly selected adult walnut trees.

b. the average height of all the adult walnut trees in this forest.

c. all the adult walnut trees in this forest.

d. the 950 adult walnut trees selected at random from this forest.

ANS: D NAT: Analytic; Statistical Inference

25. A study is under way to determine the average height of all 29,000 adult pine trees in a certain national forest. The heights of 600 randomly selected adult pine trees are measured and analyzed. The parameter in the study is:

a. the average height of the 600 randomly selected adult pine trees.

b. the average height of all the adult pine trees in this forest.

c. all the adult pine trees in this forest.

d. the 600 adult pine trees selected at random from this forest.

ANS: B NAT: Analytic; Statistical Inference

26. 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.

ANS: D NAT: Analytic; Statistical Inference

27. 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.

ANS: B NAT: Analytic; Statistical Inference

28. 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.

ANS: C NAT: Analytic; Statistical Inference

COMPLETION

29. The Owner of a large manufacturing company wishes to develop a new employee health benefits package. He selects 500 employees at random and asks them about their preferences regarding their current health benefits package. The 500 employees selected is a(n) ____________________.

ANS: sample

NAT: Analytic; Statistical Inference

30. The Human Resources Director of a large hospital wants to determine the percentage of all employees who favor a newly proposed benefits package. He selects 300 employees at random and finds that 85% approve the newly proposed package. The percentage of all employees of this company who favor the newly proposed package is a(n) ____________________.

ANS: parameter

NAT: Analytic; Statistical Inference

31. The Surgeon General wanted to study malpractice litigation in Chicago. A sample of 32,000 medical records was selected from all 3.5 million patients who were discharged during the year 2011. Using the information from the sample to make conclusions about malpractice litigation in Chicago is an example of doing ____________________ statistics.

ANS: inferential

NAT: Analytic; Statistical Inference

32. Each of the following is a form of doing ____________________ statistics: 1) presenting your data using a graph; 2) calculating the mean of your sample; and 3) organizing your data into a table.

ANS: descriptive

NAT: Analytic; Statistical Inference

33. The Commissioner of Health in the state of New York wanted to study malpractice litigation in Albany last year. She randomly selected 53,000 medical records from the population of 2.5 million patients in Albany last year. The proportion of malpractice claims filed from the 53,000 patients is an example of a(n) ____________________.

ANS: statistic

NAT: Analytic; Statistical Inference

34. The Human Resources Director at Florida Atlantic University wishes to develop an employee benefits package. To get an idea of what components of a benefits package are most important, he selects 350 employees at random and asks them for their opinions. Numerically summarizing the preferences of these 350 employees is an example of doing ____________________ statistics.

ANS: descriptive

NAT: Analytic; Statistical Inference

35. The Human Resources Director at Illinois State University wishes to develop an employee pension package. To get an idea of what components of a pension package are most important, he selects 525 employees at random and asks them for their opinions. The group of all employees at ISU is known as the ____________________.

ANS: population

NAT: Analytic; Statistical Inference

36. The Attorney General of the state of California wanted to study criminal law in Los Angeles last year. He randomly selected 46,000 criminal records from the population of 1.5 million convicts in Los Angeles last year. From this sample, he calculated the proportion of litigations, the average amount of money involved per litigation, and the proportion of litigations resulting in a conviction. These calculations are all examples of doing ____________________ statistics.

ANS: descriptive

NAT: Analytic; Statistical Inference

SHORT ANSWER

37. At Cedar Rapids Community 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 19.3 miles is computed.

a. Describe/find the parameter.

b. Describe/find the statistic.

c. Describe the population.

d. Describe the sample.

ANS:

a. The mean commute distance for all commuting students at the college.

b. 19.3 miles.

c. All commuting students enrolled at the college.

d. The 250 randomly selected commuting students.

NAT: Analytic; Statistical Inference

38. Briefly describe the difference between a parameter and a statistic, and give an example of each.

ANS:

A parameter is a descriptive measure of a population, while a statistics is a descriptive measure of a sample.

Examples: The mean number of soft drinks consumed last week by all students at Notre Dame is a parameter; the mean number of soft drinks consumed last week by a sample of 450 students from Notre Dame is a statistic.

NAT: Analytic; Statistical Inference

39. Briefly describe the difference between a population and a sample and give an example of each.

ANS:

A population is the group of all items of interest to a statistics practitioner, while a sample is a set of data drawn from a population.

Examples: All students at the West Virginia University is a population, while 150 students randomly selected from West Virginia University is a sample.

NAT: Analytic; Statistical Inference

40. What name do we give to a descriptive measure of a sample?

ANS:

A statistic.

NAT: Analytic; Statistical Inference

41. What name do we give to a descriptive measure of a population?

ANS:

A parameter.

NAT: Analytic; Statistical Inference

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