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Applied Statistics in Business and Economics David Doane 6th Edition Test Bank
Sample Questions
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Chapter 2 Data Collection
1) Categorical data have values that are described by words rather than numbers.
Answer: TRUE
Explanation: Categories are nominal data but may sometimes also be ranked (e.g., sophomore, junior, senior).
Difficulty: 1 Easy
Topic: 02.01 Variables and Data
Learning Objective: 02-02 Explain the difference between numerical and categorical data.
Bloom’s: Remember
AACSB: Analytical Thinking
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2) Numerical data can be either discrete or continuous.
Answer: TRUE
Explanation: Numerical data can be counts (e.g., cars owned) or continuous measures (e.g., height).
Difficulty: 1 Easy
Topic: 02.01 Variables and Data
Learning Objective: 02-02 Explain the difference between numerical and categorical data.
Bloom’s: Remember
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
3) Categorical data are also referred to as nominal or qualitative data.
Answer: TRUE
Explanation: Categories are nominal data (nonnumerical), sometimes called qualitative data.
Difficulty: 1 Easy
Topic: 02.01 Variables and Data
Learning Objective: 02-02 Explain the difference between numerical and categorical data.
Bloom’s: Remember
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
4) The number of checks processed at a bank in a day is an example of categorical data.
Answer: FALSE
Explanation: Integers are numerical data.
Difficulty: 1 Easy
Topic: 02.01 Variables and Data
Learning Objective: 02-02 Explain the difference between numerical and categorical data.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
5) The number of planes per day that land at an airport is an example of discrete data.
Answer: TRUE
Explanation: Integers are discrete numerical data.
Difficulty: 1 Easy
Topic: 02.01 Variables and Data
Learning Objective: 02-02 Explain the difference between numerical and categorical data.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
6) The weight of a bag of dog food is an example of discrete data.
Answer: FALSE
Explanation: Weight is measured on a continuous scale.
Difficulty: 1 Easy
Topic: 02.01 Variables and Data
Learning Objective: 02-02 Explain the difference between numerical and categorical data.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
7) In last year’s annual report, Thompson Distributors indicated that it had 12 regional warehouses. This is an example of ordinal level data.
Answer: FALSE
Explanation: “Number of” is ratio data because a zero exists.
Difficulty: 1 Easy
Topic: 02.02 Level of Measurement
Learning Objective: 02-04 Recognize levels of measurement in data and ways of coding data.
Bloom’s: Apply
AACSB: Analytical Thinking
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8) Nominal data refer to data that can be ordered in a natural way.
Answer: FALSE
Explanation: Nominal (categorical) data would be called ordinal only if categories can be ranked.
Difficulty: 1 Easy
Topic: 02.02 Level of Measurement
Learning Objective: 02-04 Recognize levels of measurement in data and ways of coding data.
Bloom’s: Remember
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
9) This year, Oxnard University produced two football All-Americans. This is an example of continuous data.
Answer: FALSE
Explanation: The “number of” anything is discrete.
Difficulty: 1 Easy
Topic: 02.01 Variables and Data
Learning Objective: 02-02 Explain the difference between numerical and categorical data.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
10) The type of statistical test that we can perform is independent of the level of measurement of the variable of interest.
Answer: FALSE
Explanation: Some statistical operations are restricted unless you have ratio or interval data.
Difficulty: 1 Easy
Topic: 02.02 Level of Measurement
Learning Objective: 02-04 Recognize levels of measurement in data and ways of coding data.
Bloom’s: Understand
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
11) Your weight recorded at your annual physical would not be ratio data, because you cannot have zero weight.
Answer: FALSE
Explanation: Zero is only a reference point, not necessarily an observable data value.
Difficulty: 2 Medium
Topic: 02.02 Level of Measurement
Learning Objective: 02-04 Recognize levels of measurement in data and ways of coding data.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
12) The level of measurement for categorical data is nominal.
Answer: TRUE
Explanation: Categorical and nominal are equivalent terms.
Difficulty: 1 Easy
Topic: 02.02 Level of Measurement
Learning Objective: 02-04 Recognize levels of measurement in data and ways of coding data.
Bloom’s: Remember
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
13) Temperature measured in degrees Fahrenheit is an example of interval data.
Answer: TRUE
Explanation: For temperature, scale distances are meaningful (20 to 25 is the same as 50 to 55 degrees), and 0 degrees Fahrenheit does not mean the absence of heat, so it is not a ratio measurement.
Difficulty: 2 Medium
Topic: 02.02 Level of Measurement
Learning Objective: 02-04 Recognize levels of measurement in data and ways of coding data.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
14) The closing price of a stock is an example of ratio data.
Answer: TRUE
Explanation: True zero exists as a reference point, whether or not it is observed.
Difficulty: 2 Medium
Topic: 02.02 Level of Measurement
Learning Objective: 02-04 Recognize levels of measurement in data and ways of coding data.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
15) The Statistical Abstract of the United States is a huge annual compendium of data for the United States, and it is available online free of charge.
Answer: FALSE
Explanation: In 2012 the U.S. Census Bureau ceased publishing this free compendium of data, but students can buy it for $199 from a private publisher.
Difficulty: 1 Easy
Topic: 02.05 Data Sources
Learning Objective: 02-08 Find everyday print or electronic data sources.
Bloom’s: Remember
AACSB: Technology
Accessibility: Keyboard Navigation
16) Ordinal data can be treated as if it were nominal data but not vice versa.
Answer: TRUE
Explanation: You can always go back to a lower level of measurement (but not vice versa).
Difficulty: 1 Easy
Topic: 02.02 Level of Measurement
Learning Objective: 02-04 Recognize levels of measurement in data and ways of coding data.
Bloom’s: Understand
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
17) Responses on a seven-point Likert scale are usually treated as ratio data.
Answer: FALSE
Explanation: No true zero point exists on a Likert scale.
Difficulty: 1 Easy
Topic: 02.02 Level of Measurement
Learning Objective: 02-04 Recognize levels of measurement in data and ways of coding data.
Bloom’s: Understand
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
18) Likert scales are especially important in opinion polls and marketing surveys.
Answer: TRUE
Explanation: Likert scales are used in all kinds of surveys.
Difficulty: 1 Easy
Topic: 02.02 Level of Measurement
Learning Objective: 02-05 Recognize a Likert scale and know how to use it.
Bloom’s: Remember
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
19) Ordinal data are data that can be ranked based on some natural characteristic of the items.
Answer: TRUE
Explanation: For example, the eras Jurassic, Paleozoic, and Mesozoic can be ranked in time.
Difficulty: 1 Easy
Topic: 02.02 Level of Measurement
Learning Objective: 02-04 Recognize levels of measurement in data and ways of coding data.
Bloom’s: Remember
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
20) Ratio data are distinguished from interval data by the presence of a zero reference point.
Answer: TRUE
Explanation: The true zero is a reference that need not be observable.
Difficulty: 2 Medium
Topic: 02.02 Level of Measurement
Learning Objective: 02-04 Recognize levels of measurement in data and ways of coding data.
Bloom’s: Remember
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
21) It is better to attempt a census of a large population instead of relying on a sample.
Answer: FALSE
Explanation: A census may flounder on cost and time, while samples can be quick and accurate.
Difficulty: 2 Medium
Topic: 02.03 Sampling Concepts
Learning Objective: 02-06 Use the correct terminology for samples and populations.
Bloom’s: Understand
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
22) Judgment sampling and convenience sampling are nonrandom sampling techniques.
Answer: TRUE
Explanation: To be random, every item must have the same chance of being chosen.
Difficulty: 1 Easy
Topic: 02.04 Sampling Methods
Learning Objective: 02-07 Explain the common sampling methods and how to implement them.
Bloom’s: Remember
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
23) A problem with judgment sampling is that the sample may not reflect the population.
Answer: TRUE
Explanation: While better than mere convenience, judgment may still have flaws.
Difficulty: 1 Easy
Topic: 02.04 Sampling Methods
Learning Objective: 02-07 Explain the common sampling methods and how to implement them.
Bloom’s: Remember
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
24) When the population is large, a sample estimate is usually preferable to a census.
Answer: TRUE
Explanation: A census may flounder on cost and time, while samples can be quick and accurate.
Difficulty: 1 Easy
Topic: 02.03 Sampling Concepts
Learning Objective: 02-06 Use the correct terminology for samples and populations.
Bloom’s: Understand
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
25) Sampling error is avoidable by choosing the sample scientifically.
Answer: FALSE
Explanation: Sampling error is unavoidable, though it can be reduced by careful sampling.
Difficulty: 2 Medium
Topic: 02.04 Sampling Methods
Learning Objective: 02-07 Explain the common sampling methods and how to implement them.
Bloom’s: Remember
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
26) A sampling frame is used to identify the target population in a statistical study.
Answer: TRUE
Explanation: Only some portion of the population may be targeted (e.g., independent voters).
Difficulty: 2 Medium
Topic: 02.03 Sampling Concepts
Learning Objective: 02-06 Use the correct terminology for samples and populations.
Bloom’s: Remember
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
27) By taking a systematic sample, in which we select every 50th shopper arriving at a specific store, we are approximating a random sample of shoppers.
Answer: TRUE
Explanation: There is no bias if this method is implemented correctly.
Difficulty: 2 Medium
Topic: 02.04 Sampling Methods
Learning Objective: 02-07 Explain the common sampling methods and how to implement them.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
28) A worker collecting data from every other shopper who leaves a store is taking a simple random sample of customer opinion.
Answer: FALSE
Explanation: Not unless the target population is customers who shopped today (cf., all customers). Also, this is a systematic (not simple) random sample.
Difficulty: 2 Medium
Topic: 02.04 Sampling Methods
Learning Objective: 02-07 Explain the common sampling methods and how to implement them.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
29) Creating a list of people by taking the third name listed on every 10th page of the phone book is an example of convenience sampling.
Answer: FALSE
Explanation: This resembles two-stage cluster sampling combined with systematic sampling.
Difficulty: 2 Medium
Topic: 02.04 Sampling Methods
Learning Objective: 02-07 Explain the common sampling methods and how to implement them.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
30) Internet surveys posted on popular websites have no bias since anyone can reply.
Answer: FALSE
Explanation: Self-selection bias exists (respondents may be atypical).
Difficulty: 2 Medium
Topic: 02.06 Surveys
Learning Objective: 02-09 Describe basic elements of survey types, survey designs, and response scales.
Bloom’s: Understand
AACSB: Technology
Accessibility: Keyboard Navigation
31) Analysis of month-by-month changes in stock market prices during the most recent recession would require the use of time series data.
Answer: TRUE
Explanation: Data collected and recorded over time would be a time series.
Difficulty: 2 Medium
Topic: 02.01 Variables and Data
Learning Objective: 02-03 Explain the difference between time series and cross-sectional data.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
32) A cluster sample is a type of stratified sample that is based on geographical location.
Answer: TRUE
Explanation: An example would be sampling voters randomly within random zip codes.
Difficulty: 1 Easy
Topic: 02.04 Sampling Methods
Learning Objective: 02-07 Explain the common sampling methods and how to implement them.
Bloom’s: Remember
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
33) An advantage of a systematic sample is that no list of enumerated data items is required.
Answer: TRUE
Explanation: Systematic sampling works with a list (like random sampling) but also without one.
Difficulty: 1 Easy
Topic: 02.04 Sampling Methods
Learning Objective: 02-07 Explain the common sampling methods and how to implement them.
Bloom’s: Remember
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
34) Telephone surveys often have a low response rate and fail to reach the desired population.
Answer: TRUE
Explanation: Phone surveys are cheaper, but suffer from these weaknesses.
Difficulty: 1 Easy
Topic: 02.06 Surveys
Learning Objective: 02-09 Describe basic elements of survey types, survey designs, and response scales.
Bloom’s: Remember
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
35) Mail surveys are attractive because of their high response rates.
Answer: FALSE
Explanation: Mail surveys have low response rates and invite self-selection bias.
Difficulty: 1 Easy
Topic: 02.06 Surveys
Learning Objective: 02-09 Describe basic elements of survey types, survey designs, and response scales.
Bloom’s: Remember
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
36) A problem with convenience sampling is that the target population is not well-defined.
Answer: TRUE
Explanation: Convenience sampling is quick but not random, and the target population is unclear.
Difficulty: 2 Medium
Topic: 02.04 Sampling Methods
Learning Objective: 02-07 Explain the common sampling methods and how to implement them.
Bloom’s: Remember
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
37) If you randomly sample 50 students about their favorite places to eat, the data collected would be referred to as cross-sectional data.
Answer: TRUE
Explanation: Data for individuals would be a cross section (not a time series).
Difficulty: 2 Medium
Topic: 02.01 Variables and Data
Learning Objective: 02-03 Explain the difference between time series and cross-sectional data.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
38) The number of FedEx shipping centers in each of 50 cities would be ordinal level data.
Answer: FALSE
Explanation: The “number of” anything is ratio data because a true zero reference point exists.
Difficulty: 2 Medium
Topic: 02.02 Level of Measurement
Learning Objective: 02-04 Recognize levels of measurement in data and ways of coding data.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
39) Internet surveys posted on popular websites suffer from nonresponse bias.
Answer: TRUE
Explanation: Nonresponse or self-selection bias is rampant in such surveys.
Difficulty: 2 Medium
Topic: 02.06 Surveys
Learning Objective: 02-09 Describe basic elements of survey types, survey designs, and response scales.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
40) Different variables are usually shown as columns of a multivariate data set.
Answer: TRUE
Explanation: It is customary to use a <i>column</i> for each variable, while each row is an <i>observation</i>.
Difficulty: 1 Easy
Topic: 02.01 Variables and Data
Learning Objective: 02-01 Use basic terminology for describing data and samples.
Bloom’s: Remember
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
41) Each row in a multivariate data matrix is an observation (e.g., an individual response).
Answer: TRUE
Explanation: It is customary to use a <i>column</i> for each variable, while each row is an <i>observation</i>.
Difficulty: 1 Easy
Topic: 02.01 Variables and Data
Learning Objective: 02-01 Use basic terminology for describing data and samples.
Bloom’s: Remember
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
42) A bivariate data set has only two observations on a variable.
Answer: FALSE
Explanation: Bivariate refers to the number of <i>variables</i>, not the number of <i>observations</i>.
Difficulty: 1 Easy
Topic: 02.01 Variables and Data
Learning Objective: 02-01 Use basic terminology for describing data and samples.
Bloom’s: Remember
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
43) Running times for 3,000 runners in a 5k race would be a multivariate data set.
Answer: FALSE
Explanation: Regardless of the number of <i>observations</i>, we have only one <i>variable</i> (running time).
Difficulty: 1 Easy
Topic: 02.01 Variables and Data
Learning Objective: 02-01 Use basic terminology for describing data and samples.
Bloom’s: Remember
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
44) Running times for 500 runners in a 5k race would be a univariate data set.
Answer: TRUE
Explanation: Regardless of the number of <i>observations</i>, we have only one <i>variable</i> (running time).
Difficulty: 1 Easy
Topic: 02.01 Variables and Data
Learning Objective: 02-01 Use basic terminology for describing data and samples.
Bloom’s: Remember
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
45) A list of the salaries, ages, and years of experience for 50 CEOs is a multivariate data set.
Answer: TRUE
Explanation: We would have a data matrix with 50 rows and 3 columns.
Difficulty: 1 Easy
Topic: 02.01 Variables and Data
Learning Objective: 02-01 Use basic terminology for describing data and samples.
Bloom’s: Remember
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
46) The daily closing price of Apple stock over the past month would be a time series.
Answer: TRUE
Explanation: Data collected over time is a time series.
Difficulty: 2 Medium
Topic: 02.01 Variables and Data
Learning Objective: 02-03 Explain the difference between time series and cross-sectional data.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
47) The number of words on 50 randomly chosen textbook pages would be cross-sectional data.
Answer: TRUE
Explanation: Data were not collected over time, so we have cross-sectional data.
Difficulty: 2 Medium
Topic: 02.01 Variables and Data
Learning Objective: 02-03 Explain the difference between time series and cross-sectional data.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
48) A Likert scale with an even number of scale points between “Strongly Agree” and “Strongly Disagree” is intended to prevent “neutral” choices.
Answer: TRUE
Explanation: An even number of scale points (e.g., 4) forces the respondent to “lean” toward one end of the scale or the other.
Difficulty: 2 Medium
Topic: 02.02 Level of Measurement
Learning Objective: 02-05 Recognize a Likert scale and know how to use it.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
49) Private statistical databases (e.g., CRSP) are usually free.
Answer: FALSE
Explanation: Private research databases generally require a subscription (often expensive).
Difficulty: 1 Easy
Topic: 02.05 Data Sources
Learning Objective: 02-08 Find everyday print or electronic data sources.
Bloom’s: Remember
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
50) An investment firm rates bonds for Aard Co Inc. as “B+,” while bonds of Deva Corp. are rated “AA.” Which level of measurement would be appropriate for such data?
- A) Nominal
- B) Ordinal
- C) Interval
- D) Ratio
Answer: B
Explanation: Ranks are clear, but interval would require assumed equal scale distances (doubtful).
Difficulty: 2 Medium
Topic: 02.02 Level of Measurement
Learning Objective: 02-04 Recognize levels of measurement in data and ways of coding data.
Bloom’s: Evaluate
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
51) Which variable is least likely to be regarded as ratio data?
- A) Length of time required for a randomly chosen vehicle to cross a toll bridge (minutes)
- B) Weight of a randomly chosen student (pounds)
- C) Number of fatalities in a randomly chosen traffic disaster (persons)
- D) Student’s evaluation of a professor’s teaching (Likert scale)
Answer: D
Explanation: A Likert scale has no true zero. The other examples do.
Difficulty: 2 Medium
Topic: 02.02 Level of Measurement
Learning Objective: 02-04 Recognize levels of measurement in data and ways of coding data.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
52) Which of the following is numerical data?
- A) Your gender
- B) The brand of cell phone you own
- C) Whether you have an American Express card
- D) The fuel economy (MPG) of your car
Answer: D
Explanation: Fuel economy is numerical. The others are categorical.
Difficulty: 1 Easy
Topic: 02.01 Variables and Data
Learning Objective: 02-02 Explain the difference between numerical and categorical data.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
53) Measurements from a sample are called
- A) statistics.
- B) inferences.
- C) parameters.
- D) variables.
Answer: A
Explanation: A measurement calculated from a sample is a statistic.
Difficulty: 1 Easy
Topic: 02.04 Sampling Methods
Learning Objective: 02-06 Use the correct terminology for samples and populations.
Bloom’s: Remember
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
54) Quantitative variables use which two levels of measurement?
- A) Ordinal and ratio
- B) Interval and ordinal
- C) Nominal and ordinal
- D) Interval and ratio
Answer: D
Explanation: Numerical (quantitative) data can be interval or ratio.
Difficulty: 2 Medium
Topic: 02.02 Level of Measurement
Learning Objective: 02-04 Recognize levels of measurement in data and ways of coding data.
Bloom’s: Remember
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
55) Temperature in degrees Fahrenheit is an example of a(n) ________ variable.
- A) nominal
- B) ordinal
- C) interval
- D) ratio
Answer: C
Explanation: No true zero exists in temperature measurements except on the Kelvin scale.
Difficulty: 1 Easy
Topic: 02.02 Level of Measurement
Learning Objective: 02-04 Recognize levels of measurement in data and ways of coding data.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
56) Using a sample to make generalizations about an aspect of a population is called
- A) data mining.
- B) descriptive statistics.
- C) random sampling.
- D) statistical inference.
Answer: D
Explanation: Generalizing from a sample to a population is an inference.
Difficulty: 1 Easy
Topic: 02.03 Sampling Concepts
Learning Objective: 02-06 Use the correct terminology for samples and populations.
Bloom’s: Remember
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
57) Your telephone area code is an example of a(n) ________ variable.
- A) nominal
- B) ordinal
- C) interval
- D) ratio
Answer: A
Explanation: Area codes are not ranked, so they are merely nominal (i.e., categorical).
Difficulty: 2 Medium
Topic: 02.02 Level of Measurement
Learning Objective: 02-04 Recognize levels of measurement in data and ways of coding data.
Bloom’s: Understand
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
58) Which is least likely to be regarded as a ratio variable?
- A) A critic’s rating of a restaurant on a 1 to 4 scale
- B) Automobile exhaust emission of nitrogen dioxide (milligrams per mile)
- C) Number of customer complaints per day at a cable TV company office
- D) Cost of an eBay purchase
Answer: A
Explanation: Ratings on a Likert scale have no meaningful zero.
Difficulty: 2 Medium
Topic: 02.02 Level of Measurement
Learning Objective: 02-04 Recognize levels of measurement in data and ways of coding data.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
59) Automobile exhaust emission of CO2 (milligrams per mile) is ________ data.
- A) nominal
- B) ordinal
- C) interval
- D) ratio
Answer: D
Explanation: Meaningful zero emissions are possible (e.g., electric car) so ratio.
Difficulty: 2 Medium
Topic: 02.02 Level of Measurement
Learning Objective: 02-04 Recognize levels of measurement in data and ways of coding data.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
60) Your rating of the food served at a local restaurant using a three-point scale of 0 = gross, 1 = decent, 2 = yummy is ________ data.
- A) nominal
- B) ordinal
- C) interval
- D) ratio
Answer: B
Explanation: Only rankings are implied (not equal scale distances).
Difficulty: 2 Medium
Topic: 02.02 Level of Measurement
Learning Objective: 02-04 Recognize levels of measurement in data and ways of coding data.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
61) The number of passengers “bumped” on a particular airline flight is ________ data.
- A) nominal
- B) ordinal
- C) interval
- D) ratio
Answer: D
Explanation: A true zero point exists (no passengers might be bumped).
Difficulty: 1 Easy
Topic: 02.02 Level of Measurement
Learning Objective: 02-04 Recognize levels of measurement in data and ways of coding data.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
62) Which should not be regarded as a continuous random variable?
- A) Tonnage carried by a randomly chosen oil tanker at sea
- B) Wind velocity at 7 o’clock this morning
- C) Number of personal fouls by the Miami Heat in a game
- D) Length of time to play a Wimbledon tennis match
Answer: C
Explanation: Counting things yields integer (discrete) data.
Difficulty: 2 Medium
Topic: 02.01 Variables and Data
Learning Objective: 02-02 Explain the difference between numerical and categorical data.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
63) Which of the following is not true?
- A) Categorical data have values that are described by words rather than numbers.
- B) Categorical data are also referred to as nominal or qualitative data.
- C) The number of checks processed at a bank in a day is categorical data.
- D) Numerical data can be either discrete or continuous.
Answer: C
Explanation: The “number of” anything is a discrete numerical variable.
Difficulty: 2 Medium
Topic: 02.01 Variables and Data
Learning Objective: 02-02 Explain the difference between numerical and categorical data.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
64) Which of the following is true?
- A) The type of charge card used by a customer (Visa, MasterCard, AmEx) is ordinal data.
- B) The duration (minutes) of a flight from Boston to Minneapolis is ratio data.
- C) The number of Nobel Prize–winning faculty at Oxnard University is continuous data.
- D) The number of regional warehouses owned by Jankord Industries is ordinal data.
Answer: B
Explanation: A true zero exists as a reference point (even if not observed), so ratios have meaning.
Difficulty: 2 Medium
Topic: 02.02 Level of Measurement
Learning Objective: 02-04 Recognize levels of measurement in data and ways of coding data.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
65) Which statement is correct?
- A) Judgment sampling is preferred to systematic sampling.
- B) Sampling without replacement introduces bias in our estimates of parameters.
- C) Cluster sampling is useful when strata characteristics are unknown.
- D) Focus groups usually work best without a moderator.
Answer: C
Explanation: Review the characteristics of each sampling method.
Difficulty: 2 Medium
Topic: 02.04 Sampling Methods
Learning Objective: 02-07 Explain the common sampling methods and how to implement them.
Bloom’s: Remember
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
66) A Likert scale
- A) yields interval data if scale distances are equal.
- B) must have an odd number of scale points.
- C) must have a verbal label on each scale point.
- D) is rarely used in marketing surveys.
Answer: A
Explanation: Marketers use Likert scales and try to make scales with meaningful intervals.
Difficulty: 2 Medium
Topic: 02.02 Level of Measurement
Learning Objective: 02-05 Recognize a Likert scale and know how to use it.
Bloom’s: Remember
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
67) Which is most nearly correct regarding sampling error?
- A) It can be eliminated by increasing the sample size.
- B) It cannot be eliminated by any statistical sampling method.
- C) It can be eliminated by using Excel’s =RANDBETWEEN() function.
- D) It can be eliminated by utilizing systematic random sampling.
Answer: B
Explanation: Sampling involves error, though it can be minimized by proper methodology.
Difficulty: 2 Medium
Topic: 02.03 Sampling Concepts
Learning Objective: 02-06 Use the correct terminology for samples and populations.
Bloom’s: Understand
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
Applied Statistics in Business and Economics, 6e (Doane)
Chapter 4 Descriptive Statistics
1) A data set with two values that are tied for the highest number of occurrences is called bimodal.
Answer: TRUE
Explanation: “Bimodal” means two modes.
Difficulty: 1 Easy
Topic: 04.02 Measures of Center
Learning Objective: 04-01 Explain the concepts of center, variability, and shape.
Bloom’s: Remember
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
2) The midrange is not greatly affected by outliers.
Answer: FALSE
Explanation: Extremes distort the midrange (average of highest and lowest data values).
Difficulty: 1 Easy
Topic: 04.02 Measures of Center
Learning Objective: 04-02 Calculate and interpret common measures of center.
Bloom’s: Remember
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
3) The second quartile is the same as the median.
Answer: TRUE
Explanation: The second quartile, the median, and the 50th percentile are the same thing.
Difficulty: 1 Easy
Topic: 04.05 Percentiles, Quartiles, and Box Plots
Learning Objective: 04-07 Calculate quartiles and other percentiles.
Bloom’s: Remember
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
4) A trimmed mean may be preferable to a mean when a data set has extreme values.
Answer: TRUE
Explanation: Trimming diminishes the effect of outliers.
Difficulty: 1 Easy
Topic: 04.02 Measures of Center
Learning Objective: 04-02 Calculate and interpret common measures of center.
Bloom’s: Understand
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
5) One benefit of the box plot is that it clearly displays the standard deviation.
Answer: FALSE
Explanation: A box plot shows quartiles.
Difficulty: 2 Medium
Topic: 04.05 Percentiles, Quartiles, and Box Plots
Learning Objective: 04-08 Make and interpret box plots.
Bloom’s: Understand
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
6) It is inappropriate to apply the Empirical Rule to a population that is right-skewed.
Answer: TRUE
Explanation: The Empirical Rule applies to normal populations.
Difficulty: 2 Medium
Topic: 04.04 Standardized Data
Learning Objective: 04-05 Apply the Empirical Rule and recognize outliers.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
7) Given the data set 10, 5, 2, 6, 3, 4, 20, the median value is 5.
Answer: TRUE
Explanation: Sort and find the middle value.
Difficulty: 2 Medium
Topic: 04.02 Measures of Center
Learning Objective: 04-02 Calculate and interpret common measures of center.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
8) Given the data set 2, 5, 10, 6, 3, the median value is 3.
Answer: FALSE
Explanation: Sort and find the middle value: 2 3 5 6 10.
Difficulty: 2 Medium
Topic: 04.02 Measures of Center
Learning Objective: 04-02 Calculate and interpret common measures of center.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
9) When data are right-skewed, we expect the median to be greater than the mean.
Answer: FALSE
Explanation: It is the other way around, as the mean will be pulled up by extremes.
Difficulty: 1 Easy
Topic: 04.02 Measures of Center
Learning Objective: 04-01 Explain the concepts of center, variability, and shape.
Bloom’s: Remember
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
10) The sum of the deviations around the mean is always zero.
Answer: TRUE
Explanation: The mean is the fulcrum (balancing point), so deviations must sum to zero.
Difficulty: 2 Medium
Topic: 04.02 Measures of Center
Learning Objective: 04-02 Calculate and interpret common measures of center.
Bloom’s: Remember
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
11) The midhinge is a robust measure of center when there are outliers.
Answer: TRUE
Explanation: Outliers have little effect on the midhinge (average of the 25th and 75th percentiles).
Difficulty: 2 Medium
Topic: 04.05 Percentiles, Quartiles, and Box Plots
Learning Objective: 04-07 Calculate quartiles and other percentiles.
Bloom’s: Understand
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
12) Chebyshev’s Theorem says that at most 50 percent of the data lie within 2 standard deviations of the mean.
Answer: FALSE
Explanation: At least 75 percent by Chebyshev.
Difficulty: 2 Medium
Topic: 04.04 Standardized Data
Learning Objective: 04-04 Apply Chebyshev’s theorem.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
13) Chebyshev’s Theorem says that at least 95 percent of the data lie within 2 standard deviations of the mean.
Answer: FALSE
Explanation: At least 75 percent by Chebyshev.
Difficulty: 2 Medium
Topic: 04.04 Standardized Data
Learning Objective: 04-04 Apply Chebyshev’s theorem.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
14) If there are 19 data values, the median will have 10 values above it and 9 below it since nis odd.
Answer: FALSE
Explanation: When n is odd, the median is the middle member of the sorted data set. In this case, the median is x10 and there will be 9 below x10 (x1, . . . ,x9) and 9 above x10 (x11, . . . , x19).
Difficulty: 2 Medium
Topic: 04.02 Measures of Center
Learning Objective: 04-02 Calculate and interpret common measures of center.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
15) If there are 20 data values, the median will be halfway between two data values.
Answer: TRUE
Explanation: Median is between two data values when n is even.
Difficulty: 2 Medium
Topic: 04.02 Measures of Center
Learning Objective: 04-02 Calculate and interpret common measures of center.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
16) In a left-skewed distribution, we expect that the median will be greater than the mean.
Answer: TRUE
Explanation: The mean is likely to be pulled down by low extremes.
Difficulty: 1 Easy
Topic: 04.02 Measures of Center
Learning Objective: 04-01 Explain the concepts of center, variability, and shape.
Bloom’s: Understand
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
17) If the standard deviations of two samples are the same, so are their coefficients of variation.
Answer: FALSE
Explanation: The means may differ, which affects their coefficients of variation.
Difficulty: 2 Medium
Topic: 04.03 Measures of Variability
Learning Objective: 04-03 Calculate and interpret common measures of variability.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
18) A certain health maintenance organization (HMO) examined the number of office visits by its members in the last year. This data set would probably be skewed to the left due to low outliers.
Answer: FALSE
Explanation: The lower bound is zero, but high extremes are likely for sicker individuals.
Difficulty: 3 Hard
Topic: 04.02 Measures of Center
Learning Objective: 04-01 Explain the concepts of center, variability, and shape.
Bloom’s: Evaluate
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
19) A certain health maintenance organization examined the number of office visits by its members in the last year. For this data set, the mean is probably not a very good measure of a “typical” person’s office visits.
Answer: TRUE
Explanation: The lower bound is zero, but high extremes are likely for sicker individuals.
Difficulty: 3 Hard
Topic: 04.02 Measures of Center
Learning Objective: 04-02 Calculate and interpret common measures of center.
Bloom’s: Evaluate
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
20) Referring to this box plot of ice cream fat content, the median seems more “typical” of fat content than the midrange as a measure of center.
Answer: TRUE
Explanation: The midrange (average of low and high) will be pulled down by the left-tail minimum in this left-skewed distribution.
Difficulty: 2 Medium
Topic: 04.05 Percentiles, Quartiles, and Box Plots
Learning Objective: 04-08 Make and interpret box plots.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
21) Referring to this box plot of ice cream fat content, the mean would exceed the median.
Answer: FALSE
Explanation: The data are skewed left.
Difficulty: 2 Medium
Topic: 04.05 Percentiles, Quartiles, and Box Plots
Learning Objective: 04-08 Make and interpret box plots.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
22) Referring to this box plot of ice cream fat content, the skewness would be negative.
Answer: TRUE
Explanation: The data are skewed left (negative skewness) as indicated by the long left tail.
Difficulty: 2 Medium
Topic: 04.05 Percentiles, Quartiles, and Box Plots
Learning Objective: 04-08 Make and interpret box plots.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
23) Referring to this graph of ice cream fat content, the second quartile is between 60 and 61.
Answer: TRUE
Explanation: Drop a line to lower axis to hit between 60 and 61.
Difficulty: 2 Medium
Topic: 04.05 Percentiles, Quartiles, and Box Plots
Learning Objective: 04-08 Make and interpret box plots.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
24) The range as a measure of variability is very sensitive to extreme data values.
Answer: TRUE
Explanation: The range depends only on highest and lowest data values, so it is easily distorted.
Difficulty: 1 Easy
Topic: 04.03 Measures of Variability
Learning Objective: 04-03 Calculate and interpret common measures of variability.
Bloom’s: Understand
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
25) In calculating the sample variance, the sum of the squared deviations around the mean is divided by n − 1 to avoid underestimating the unknown population variance.
Answer: TRUE
Explanation: Check the definition. You lose one piece of information because the mean is estimated.
Difficulty: 2 Medium
Topic: 04.03 Measures of Variability
Learning Objective: 04-03 Calculate and interpret common measures of variability.
Bloom’s: Understand
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
26) Outliers are data values that fall beyond ±2 standard deviations from the mean.
Answer: FALSE
Explanation: Outliers are 3 standard deviations from the mean
Difficulty: 1 Easy
Topic: 04.04 Standardized Data
Learning Objective: 04-05 Apply the Empirical Rule and recognize outliers.
Bloom’s: Remember
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
27) The Empirical Rule assumes that the distribution of data follows a normal curve.
Answer: TRUE
Explanation: Unlike Chebyshev, the Empirical Rule assumes a normal population.
Difficulty: 1 Easy
Topic: 04.04 Standardized Data
Learning Objective: 04-05 Apply the Empirical Rule and recognize outliers.
Bloom’s: Remember
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
28) The Empirical Rule can be applied to any distribution, unlike Chebyshev’s theorem.
Answer: FALSE
Explanation: The Empirical Rule assumes a normal population, while Chebyshev applies to any population.
Difficulty: 2 Medium
Topic: 04.04 Standardized Data
Learning Objective: 04-05 Apply the Empirical Rule and recognize outliers.
Bloom’s: Understand
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
29) When applying the Empirical Rule to a distribution of grades, if a student scored one standard deviation below the mean, then she would be at the 25th percentile of the distribution.
Answer: FALSE
Explanation: About 15.87 percent (not 25 percent) are less than one standard deviation below the mean (in a normal distribution).
Difficulty: 2 Medium
Topic: 04.04 Standardized Data
Learning Objective: 04-05 Apply the Empirical Rule and recognize outliers.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
30) Kurtosis cannot be judged accurately by looking at a histogram.
Answer: TRUE
Explanation: Histograms are affected by scaling, so peakedness is hard to judge.
Difficulty: 2 Medium
Topic: 04.08 Skewness and Kurtosis
Learning Objective: 04-11 Assess skewness and kurtosis in a sample.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
31) A platykurtic distribution is more sharply peaked (i.e., thinner tails) than a normal distribution.
Answer: FALSE
Explanation: A platykurtic distribution is flatter than a normal distribution (thicker tails).
Difficulty: 2 Medium
Topic: 04.08 Skewness and Kurtosis
Learning Objective: 04-11 Assess skewness and kurtosis in a sample.
Bloom’s: Remember
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
32) A leptokurtic distribution is more sharply peaked (i.e., thinner tails) than a normal distribution.
Answer: TRUE
Explanation: A leptokurtic distribution is more sharply peaked and has thinner tails.
Difficulty: 2 Medium
Topic: 04.08 Skewness and Kurtosis
Learning Objective: 04-11 Assess skewness and kurtosis in a sample.
Bloom’s: Remember
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
33) A positive kurtosis coefficient in Excel indicates a leptokurtic condition in a distribution.
Answer: TRUE
Explanation: The sign of Excel’s kurtosis coefficient indicates the kurtosis direction relative to a normal distribution.
Difficulty: 2 Medium
Topic: 04.08 Skewness and Kurtosis
Learning Objective: 04-11 Assess skewness and kurtosis in a sample.
Bloom’s: Remember
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
34) A sample consists of the following data: 7, 11, 12, 18, 20, 22, 43. Using the “three standard deviation” criterion, the last observation (X = 43) would be considered an outlier.
Answer: FALSE
Explanation: The observation 43 is not more than three standard deviations above the mean for this data set. The sample mean is 19.00 and the sample standard deviation is 11.86.
Difficulty: 3 Hard
Topic: 04.04 Standardized Data
Learning Objective: 04-06 Transform a data set into standardized values.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
35) The coefficient of variation is
- A) measured on a scale from 0 to 100.
- B) a unit-free statistic.
- C) helpful when the sample means are zero.
- D) a measure of correlation for two variables.
Answer: B
Explanation: The coefficient of variation is unit free. It is the standard deviation as a percentage of the mean. But it cannot be used when the mean is zero because the mean is in the denominator.
Difficulty: 1 Easy
Topic: 04.03 Measures of Variability
Learning Objective: 04-03 Calculate and interpret common measures of variability.
Bloom’s: Remember
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
36) Which is not an advantage of the method of medians to find Q1 and Q3?
- A) Ease of interpolating quartile positions
- B) Ease of application in small data sets
- C) Intuitive definitions without complex formulas
- D) Same method as Excel’s =QUARTILE.EXC function.
Answer: D
Explanation: When the quartiles lie between two data values, the method of medians goes halfway between the values (very simple), while Excel interpolates between them in a more complex way.
Difficulty: 2 Medium
Topic: 04.05 Percentiles, Quartiles, and Box Plots
Learning Objective: 04-07 Calculate quartiles and other percentiles.
Bloom’s: Understand
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
37) Which is a characteristic of the mean as a measure of center?
- A) Deviations do not sum to zero when there are extreme values.
- B) It is less reliable than the mode when the data are continuous.
- C) It utilizes all the information in a sample.
- D) It is usually equal to the median in business data.
Answer: C
Explanation: The mean utilizes all n data values. Deviations always sum to zero around the mean. The mean works for continuous data (unlike the mode). The mean often differs from the median in business data.
Difficulty: 2 Medium
Topic: 04.02 Measures of Center
Learning Objective: 04-02 Calculate and interpret common measures of center.
Bloom’s: Understand
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
38) The position of the median is
- A) n/2 in any sample.
- B) n/2 if n is even.
- C) n/2 if n is odd.
- D) (n+1)/2 in any sample.
Answer: D
Explanation: This formula always works for the median position. For example, if n = 10 (even) the median is at position (10+1)/2 = 5.5, or halfway between x5 and x6. But if n = 11 (odd) the median is at position (11+1)/2 = 6, which is observation x6.
Difficulty: 3 Hard
Topic: 04.02 Measures of Center
Learning Objective: 04-02 Calculate and interpret common measures of center.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
39) Which is a characteristic of the trimmed mean as a measure of center?
- A) It is similar to the mean if there are offsetting high and low extremes.
- B) It is especially helpful in a small sample.
- C) It does not require sorting the sample.
- D) It is basically the same as the midrange.
Answer: A
Explanation: After sorting, we can trim unusual values to stabilize the mean. The trimmed mean may be similar to the mean if the extremes on either end offset each other. Unlike the trimmed mean, the midrange is affected by outliers.
Difficulty: 2 Medium
Topic: 04.02 Measures of Center
Learning Objective: 04-02 Calculate and interpret common measures of center.
Bloom’s: Understand
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
40) Which is not a characteristic of the geometric mean as a measure of center?
- A) It is similar to the mean if the data are skewed right.
- B) It mitigates the effects of large data values.
- C) It is useful in business data to calculate average growth rates.
- D) It cannot be calculated when the data contain negative or zero values.
Answer: A
Explanation: Although both the mean and the geometric mean are affected by high extremes in skewed data, the geometric mean tends to reduce their influence. The geometric mean cannot be used when any data values are zero or negative.
Difficulty: 2 Medium
Topic: 04.02 Measures of Center
Learning Objective: 04-02 Calculate and interpret common measures of center.
Bloom’s: Understand
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
41) Which is not a characteristic of the standard deviation?
- A) It is always the square root of the variance.
- B) It is not applicable when data are continuous.
- C) It can be calculated when the data contain negative or zero values.
- D) Its physical interpretation is not as easy as the MAD.
Answer: B
Explanation: The standard deviation applies to any data measured on a ratio or interval scale. Because it is a square root, its visual interpretation may be less clear than the MAD.
Difficulty: 2 Medium
Topic: 04.03 Measures of Variability
Learning Objective: 04-03 Calculate and interpret common measures of variability.
Bloom’s: Remember
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
42) Chebyshev’s Theorem
- A) applies to all samples.
- B) applies only to samples from a normal population.
- C) gives a narrower range of predictions than the Empirical Rule.
- D) is based on Sturges’ Rule for data classification.
Answer: A
Explanation: The strength of Chebyshev’s Theorem is that it makes no assumption about normality, while the Empirical Rule only works for normal populations.
Difficulty: 2 Medium
Topic: 04.04 Standardized Data
Learning Objective: 04-04 Apply Chebyshev’s theorem.
Bloom’s: Remember
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
43) Which of the following is not a valid description of an outlier?
- A) A data value beyond the outer fences
- B) A data value that is very unusual
- C) A data value that lies below Q1or above Q3
- D) A data value several standard deviations from the mean.
Answer: C
Explanation: Data values outside the quartiles (top or bottom 25 percent) are not very unusual.
Difficulty: 2 Medium
Topic: 04.04 Standardized Data
Learning Objective: 04-05 Apply the Empirical Rule and recognize outliers.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
44) If samples are from a normal distribution with μ = 100 and σ = 10, we expect
- A) about 68 percent of the data within 90 to 110.
- B) almost all the data within 80 to 120.
- C) about 95 percent of the data within 70 to 130.
- D) about half the data to exceed 75.
Answer: A
Explanation: Review the Empirical Rule. For example, the interval 90 to 110 is the μ ± 1σ range.
Difficulty: 2 Medium
Topic: 04.04 Standardized Data
Learning Objective: 04-05 Apply the Empirical Rule and recognize outliers.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
45) In a sample of 10,000 observations from a normal population, how many would you expect to lie beyond three standard deviations of the mean?
- A) None of them
- B) About 27
- C) About 100
- D) About 127
Answer: B
Explanation: Within μ ± 3σ we would expect 99.73 percent of 10,000, or 9,973 data values.
Difficulty: 2 Medium
Topic: 04.04 Standardized Data
Learning Objective: 04-05 Apply the Empirical Rule and recognize outliers.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
46) Which is the Excel formula for the standard deviation of a sample array named Data?
- A) =STDEV.S(Data)
- B) =STANDEV(Data)
- C) =STDEV.P(Data)
- D) =SUM(Data)/(COUNT(Data)-1)
Answer: A
Explanation: STDEV.S(Data) denotes a sample standard deviation.
Difficulty: 2 Medium
Topic: 04.03 Measures of Variability
Learning Objective: 04-03 Calculate and interpret common measures of variability.
Bloom’s: Remember
AACSB: Technology
Accessibility: Keyboard Navigation
47) Which is not true of an outlier?
- A) It is likely to be from a different population.
- B) It suggests an error in recording the data.
- C) It is best discarded to get a better mean.
- D) It is an anomaly that may tell the researcher something.
Answer: C
Explanation: We are reluctant to delete outliers, as they may tell us something important.
Difficulty: 1 Easy
Topic: 04.04 Standardized Data
Learning Objective: 04-05 Apply the Empirical Rule and recognize outliers.
Bloom’s: Understand
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
48) Estimating the mean from grouped data will tend to be most accurate when
- A) observations are distributed uniformly within classes.
- B) there are few classes with wide class limits.
- C) the sample is not very large and bins are wide.
- D) the standard deviation is large relative to the mean.
Answer: A
Explanation: Many bins and uniform data distribution within bins would give a result closest to the ungrouped mean μ.
Difficulty: 1 Easy
Topic: 04.07 Grouped Data
Learning Objective: 04-10 Calculate the mean and standard deviation from grouped data.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
49) Which is true of the kurtosis of a distribution?
- A) A distribution that is flatter than a normal distribution (i.e., thicker tails) is mesokurtic.
- B) A distribution that is more peaked than a normal distribution (i.e., thinner tails) is platykurtic.
- C) It is risky to assess kurtosis if the sample size is less than 50.
- D) The expected range of the kurtosis coefficient increases as n
Answer: C
Explanation: Shape is hard to judge in small samples. Excel computes kurtosis for samples of any size, but tables of critical values may not go down below n = 50.
Difficulty: 3 Hard
Topic: 04.08 Skewness and Kurtosis
Learning Objective: 04-11 Assess skewness and kurtosis in a sample.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
50) Which is true of skewness?
- A) In business data, positive skewness is unusual.
- B) In a negatively skewed distribution, the mean is likely to exceed the median.
- C) Skewness often is evidenced by one or more outliers.
- D) The expected range of Excel’s skewness coefficient increases as n
Answer: C
Explanation: Skewness due to extreme data values is common in business data. Right skewness is common, which increases the mean relative to the median.
Difficulty: 3 Hard
Topic: 04.08 Skewness and Kurtosis
Learning Objective: 04-11 Assess skewness and kurtosis in a sample.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
51) Which is not true of the Empirical Rule?
- A) It applies to any distribution.
- B) It can be applied to fewer distributions than Chebyshev’s Theorem.
- C) It assumes that the distribution of data follows a bell-shaped, normal curve.
- D) It predicts more observations within μ ± kσ than Chebyshev’s Theorem.
Answer: A
Explanation: The Empirical Rule applies only to normal populations, while Chebyshev’s Theorem is general.
Difficulty: 2 Medium
Topic: 04.04 Standardized Data
Learning Objective: 04-05 Apply the Empirical Rule and recognize outliers.
Bloom’s: Understand
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
52) Which is a correct statement concerning the median?
- A) In a left-skewed distribution, we expect that the median will exceed the mean.
- B) The sum of the deviations around the median is zero.
- C) The median is an observed data value in any data set.
- D) The median is halfway between Q1and Q3on a box plot.
Answer: A
Explanation: The mean is pulled down in left-skewed data, but deviations around it sum to zero in any data set. The median may be between two data values and may not be in the middle of the box plot.
Difficulty: 2 Medium
Topic: 04.02 Measures of Center
Learning Objective: 04-02 Calculate and interpret common measures of center.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
53) Which statement is true?
- A) With nominal data, we can find the mode.
- B) Outliers distort the mean, but not the standard deviation.
- C) Business and economic data are rarely skewed to the right.
- D) If we sample a normal population, the sample skewness coefficient is exactly 0.
Answer: A
Explanation: The mode (most frequent data value) works for nominal data. Outliers affect both the mean and the standard deviation. Skewness will be near zero in samples from a normal population, but not exactly due to sample variation.
Difficulty: 2 Medium
Topic: 04.02 Measures of Center
Learning Objective: 04-02 Calculate and interpret common measures of center.
Bloom’s: Understand
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
54) Exam scores in a small class were 10, 10, 20, 20, 40, 60, 80, 80, 90, 100, 100. For this data set, which statement is incorrect concerning measures of center?
- A) The median is 60.00.
- B) The mode is not helpful.
- C) The 5 percent trimmed mean would be awkward.
- D) The geometric mean is 35.05.
Answer: D
Explanation: To find the geometric mean, multiply the data values and take the 11th root to get G = 41.02. Outliers affect both the mean and the standard deviation. There are multiple modes in this example.
Difficulty: 3 Hard
Topic: 04.02 Measures of Center
Learning Objective: 04-02 Calculate and interpret common measures of center.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
55) Exam scores in a small class were 0, 50, 50, 70, 70, 80, 90, 90, 100, 100. For this data set, which statement is incorrect concerning measures of center?
- A) The median is 70.
- B) The mode is not helpful.
- C) The geometric mean is useless.
- D) The mean is 70.
Answer: A
Explanation: The median is 75 (halfway between x5 = 70 and x6 = 80 in the sorted array). The zeros render the geometric mean useless. The modes in this case are not unique.
Difficulty: 3 Hard
Topic: 04.02 Measures of Center
Learning Objective: 04-02 Calculate and interpret common measures of center.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
56) Exam scores in a random sample of students were 0, 50, 50, 70, 70, 80, 90, 90, 90, 100. Which statement is incorrect?
- A) The standard deviation is 29.61.
- B) The data are slightly left-skewed.
- C) The midrange and mean are almost the same.
- D) The third quartile is 90.
Answer: C
Explanation: The midrange is (0 + 100)/2 = 50, while the mean is 69. Q3 falls between 90 and 90.
Difficulty: 2 Medium
Topic: 04.02 Measures of Center
Learning Objective: 04-02 Calculate and interpret common measures of center.
Bloom’s: Apply
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
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