Marketing Chapter 17 Locating Blunders Locating Outliers Answer Rationale All These Are Uses For Frequency

Document Type
Test Prep
Book Title
Basic Marketing Research 9th Edition
Authors
Gilbert A. Churchill, Tom J. Brown, Tracy A. Suter
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Page 1
1. Data analysis hinges on which of the following considerations about the variable(s) to be analyzed?
a.
Will the variable be analyzed in isolation or in relationship to one or more other variables?
b.
What type of analysis is required by the project sponsor?
c.
What level of measurement was used to measure the variable(s)?
d.
What level of measurement was used to measure the variable(s)?
e.
All of these are considerations about the variable(s) to be analyzed.
ANSWER:
d
RATIONALE:
The considerations, “Will the variable be analyzed in isolation or in relationship
to one or more other variables?” and “What level of measurement was used to
measure the variable(s)?” are crucial for data analysis. See 17-1: Basic
Univariate Statistics: Categorical Measures.
POINTS:
1
DIFFICULTY:
Easy
REFERENCES:
Remember
QUESTION TYPE:
Multiple Choice
HAS VARIABLES:
False
ACCREDITING STANDARDS:
17.01 - Distinguish between univariate and multivariate analyses.
DATE CREATED:
7/31/2017 3:20 AM
DATE MODIFIED:
7/31/2017 3:22 AM
2. Univariate analysis refers to analyzing
a.
the relationship between variables.
b.
a variable in isolation.
c.
the unit variation for a variable.
d.
All of these are correct.
e.
None of these are correct.
b
Univariate analysis refers to analyzing a variable in isolation. See 17-1: Basic Univariate
Statistics: Categorical Measures.
1
Easy
Remember
Multiple Choice
False
17.01 - Distinguish between univariate and multivariate analyses.
7/31/2017 3:23 AM
9/21/2017 11:12 AM
3. Which of the following would NOT be an example of a situation involving univariate analysis?
a.
A publisher of a magazine is interested in determining what proportion of the magazine's readers is male.
b.
A restaurant would like to know the average income of its typical diner.
c.
A car dealership is particularly interested in whether or not people who own vans are more or less likely to
finance auto purchases compared with people who don't own vans.
d.
A service provider needs to know her customer's average level of satisfaction with the services provided.
e.
All of these are examples for which univariate analysis could be performed.
c
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Page 2
All of these are examples of situations involving univariate analysis except for the situation
where a car dealership is particularly interested in whether or not people who own vans are
more or less likely to finance auto purchases compared with people who don't own vans.
See 17-1: Basic Univariate Statistics: Categorical Measures.
1
Easy
Apply
Multiple Choice
False
17.01 - Distinguish between univariate and multivariate analyses.
7/31/2017 3:36 AM
7/31/2017 3:40 AM
4. Which types of measurement are used to group respondents or objects into groups or categories and are thus referred to
as categorical measures?
a.
Nominal and interval
b.
Ordinal and ratio
c.
Ratio and interval
d.
Nominal and ordinal
e.
Ordinal and interval
d
This describes nominal and ordinal measurements. See 17-1: Basic Univariate Statistics:
Categorical Measures.
1
Easy
Understand
Multiple Choice
False
17.01 - Distinguish between univariate and multivariate analyses.
7/31/2017 4:50 AM
7/31/2017 4:53 AM
5. A frequency analysis is NOT used to
a.
locate blunders.
b.
locate outliers.
c.
determine the empirical distribution of the variable.
d.
communicate the results of the study.
e.
determine the relationship between two variables.
e
All of these are uses of frequency analysis except to determine the relationship between
two variables. See 17-1: Basic Univariate Statistics: Categorical Measures.
1
Easy
Understand
Multiple Choice
False
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Page 3
17.02 - Describe frequency analysis.
7/31/2017 4:58 AM
7/31/2017 5:02 AM
6. A frequency analysis is useful for
a.
locating blunders.
b.
determining the empirical distribution of the variable in question.
c.
determining the relationship between two variables.
d.
locating blunders and determining the empirical distribution of the variable in question.
e.
All of these are correct.
d
A frequency analysis is useful for locating blunders and determining the empirical
distribution of the variable in question. See 17-1: Basic Univariate Statistics:
Categorical Measures.
1
Easy
Remember
Multiple Choice
False
17.02 - Describe frequency analysis.
7/31/2017 5:14 AM
9/21/2017 11:13 AM
7. A frequency analysis reveals that the percentage of men owning Dalmatians is 9.93472. Which of the following is the
best way to display this finding?
a.
9.93472%
b.
9.93%
c.
10%
d.
9%
e.
9.9%
c
The best way to display this value would be 10%. See 17-1: Basic Univariate
Statistics: Categorical Measures.
1
Easy
Apply
Multiple Choice
False
17.02 - Describe frequency analysis.
7/31/2017 5:18 AM
7/31/2017 5:19 AM
8. An observation that is very different in magnitude from the rest of the observations for a particular variable is a(n)
a.
error.
b.
blunder.
c.
histogram.
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Page 4
d.
outlier.
e.
deviant.
d
An observation that is very different in magnitude from the rest of the observations
for a particular variable is an outlier. See 17-1: Basic Univariate Statistics:
Categorical Measures.
1
Easy
Remember
Multiple Choice
False
17.02 - Describe frequency analysis.
7/31/2017 5:31 AM
7/31/2017 5:32 AM
9. A bar chart where the values of a variable are placed along the X-axis and the absolute or relative frequency along the
Y-axis is called a ____ and can be developed from the ____.
a.
bar graph, cumulative data
b.
frequency polygon, one-way frequency tabulation
c.
cumulative distribution graph, cumulative data
d.
histogram, uncoded data
e.
histogram, one-way frequency tabulation
e
A bar chart where the values of a variable are placed along the X-axis and the
absolute or relative frequency along the Y-axis is called a histogram and can be
developed from the one-way frequency tabulation. See 17-1: Basic Univariate
Statistics: Categorical Measures.
1
Easy
Remember
Multiple Choice
False
17.02 - Describe frequency analysis.
7/31/2017 5:35 AM
7/31/2017 5:37 AM
10. Histograms are used to
a.
investigate the relation between two variables.
b.
construct cumulative distribution functions.
c.
construct cross tabulation tables.
d.
determine the distribution of nonresponse errors.
e.
determine the empirical distribution of a variable.
e
Histograms are used to determine the empirical distribution of a variable. See 17-
1: Basic Univariate Statistics: Categorical Measures.
1
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Page 5
Easy
Remember
Multiple Choice
False
17.02 - Describe frequency analysis.
7/31/2017 5:43 AM
7/31/2017 5:44 AM
11. Categorical measures are most commonly used to
a.
calculate confidence intervals.
b.
group respondents or objects into groups.
c.
determine the standard deviation.
d.
develop histograms.
e.
All of these are correct.
b
Categorical measures are most commonly used to group respondents or objects
into groups. See 17-1: Basic Univariate Statistics: Categorical Measures.
1
Easy
Remember
Multiple Choice
False
17.01 - Distinguish between univariate and multivariate analyses.
7/31/2017 5:46 AM
7/31/2017 5:47 AM
12. It is possible to produce frequencies for
a.
nominal measures only.
b.
ordinal measures only.
c.
categorical measures only.
d.
any variables in a study.
e.
None of these are correct.
d
It is possible to produce frequencies for any variables in a study. See 17-1: Basic
Univariate Statistics: Categorical Measures.
1
Easy
Remember
Multiple Choice
False
17.02 - Describe frequency analysis.
7/31/2017 5:51 AM
9/21/2017 11:14 AM
13. For which of the following is frequency analysis NOT useful?
a.
Understanding the relationship between two variables
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Page 6
b.
Communicating the results of a study
c.
Determining the degree of item nonresponse
d.
Locating blunders
e.
Locating outliers
a
All of these are uses for frequency analysis except understanding the relationship
between two variables. See 17-1: Basic Univariate Statistics: Categorical
Measures.
1
Easy
Understand
Multiple Choice
False
17.02 - Describe frequency analysis.
7/31/2017 5:56 AM
7/31/2017 5:57 AM
14. When performing frequency analysis
a.
you'll almost always want to include percentages along with the raw count.
b.
including percentages will help readers interpret results.
c.
the number of missing cases should be indicated.
d.
All of these are correct.
e.
None of these are correct.
d
All of these describe frequency analysis. See 17-1: Basic Univariate Statistics:
Categorical Measures.
1
Easy
Understand
Multiple Choice
False
17.02 - Describe frequency analysis.
7/31/2017 5:58 AM
9/21/2017 11:14 AM
15. Some of the commonly used measures of location such as the median or quartiles can be read directly from a
a.
matrix.
b.
frequency polygon.
c.
histogram.
d.
cumulative distribution function.
e.
contingency table.
d
This describes the cumulative distribution function. See 17-2: Basic Univariate
Statistics: Continuous Measures.
1
Easy
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Page 7
Understand
Multiple Choice
False
17.03 - Describe descriptive statistics
7/31/2017 6:02 AM
7/31/2017 6:04 AM
16. A researcher is interested in analyzing a set of nominal data to determine if the observed pattern of frequencies
corresponds to the expected pattern. The appropriate statistical technique is
a.
chi-square goodness-of-fit.
b.
regression analysis.
c.
z-test for comparing sample proportion against a standard.
d.
z-test for comparing sample mean against a standard.
e.
frequency analysis.
a
This describes chi-square goodness-of-fit. See 17-4: Testing Hypotheses About
Individual Variables.
1
Easy
Apply
Multiple Choice
False
17.05 - Overview the basic purpose of hypothesis testing.
7/31/2017 6:16 AM
7/31/2017 6:17 AM
17. A major car manufacturer was interested in whether its midsize car was selling consistently in two markets with
respect to the annual income of the car purchasers. Five-hundred new car buyers in Chicago and Miami were surveyed. In
Chicago, the following pattern was observed: < $20,000 5%; $20,000-$29,999 0%; $30,000-$39,999 40%; $40,000-
$49,999 30%; $50,000 5%. Among those surveyed in Miami, 20 earned under $20,000; 70 earned between $20,000 and
$30,000; 265 earned between $30,000 and $40,000; 125 earned between $40,000 and $50,000; and 20 earned more than
$50,000. The chi-square test was used to check whether Miami sales among income groups were consistent with
Chicago's. The appropriate degrees of freedom for the chi-square test would be
a.
4
b.
5
c.
500
d.
499
e.
None of these are correct.
a
The appropriate degrees of freedom for the chi-square test would be 4. See 17-4:
Testing Hypotheses About Individual Variables.
1
Easy
Apply
Multiple Choice
False
17.05 - Overview the basic purpose of hypothesis testing.
Copyright Cengage Learning. Powered by Cognero.
Page 8
7/31/2017 6:20 AM
7/31/2017 6:21 AM
18. A major car manufacturer was interested in whether its midsize car was selling consistently in two markets with
respect to the annual income of the car purchasers. Five-hundred new car buyers in Chicago and Miami were surveyed. In
Chicago, the following pattern was observed: < $20,000 5%; $20,000-$29,999 0%; $30,000-$39,999 40%; $40,000-
$49,999 30%; $50,000 5%. Among those surveyed in Miami, 20 earned under $20,000; 70 earned between $20,000 and
$30,000; 265 earned between $30,000 and $40,000; 125 earned between $40,000 and $50,000; and 20 earned more than
$50,000. Using the data provided, the calculated value of |2 =
a.
0.883
b.
36.30
c.
11.95
d.
−0.542
e.
Not enough information is provided to calculate the value.
b
The calculated value of |2 would be 36.30. See 17-4: Testing Hypotheses About
Individual Variables.
1
Easy
Apply
Multiple Choice
False
17.05 - Overview the basic purpose of hypothesis testing.
7/31/2017 6:29 AM
7/31/2017 6:30 AM
19. Which statement(s) pertaining to the chi-square distribution is FALSE?
a.
The chi-square distribution is completely determined by its degrees of freedom.
b.
The variable of interest is broken into k mutually exclusive categories.
c.
The expected number falling into a category is generated from the null hypothesis.
d.
The chi-square degrees of freedom are given by k - 2.
e.
The chi-square is appropriate for independent trials.
d
All of the statements are true except that the chi-square degrees of freedom are
given by k 2. See 17-4: Testing Hypotheses About Individual Variables.
1
Easy
Understand
Multiple Choice
False
17.05 - Overview the basic purpose of hypothesis testing.
7/31/2017 6:34 AM
7/31/2017 6:35 AM
20. The chi-square test is an approximate test. The approximation is relatively good if the
a.
expected number of cases in each category is 10 or more.
b.
expected number of cases in each category is 5 or more.
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Page 9
c.
expected number of cases in each category is 3 or more.
d.
actual number of cases in each category is 10 or more.
e.
actual number of cases in each category is 5 or more.
b
The approximation is relatively good if the expected number of cases in each
category is 5 or more. See 17-4: Testing Hypotheses About Individual Variables.
1
Easy
Understand
Multiple Choice
False
17.05 - Overview the basic purpose of hypothesis testing.
7/31/2017 6:44 AM
7/31/2017 6:45 AM
21. A researcher calculates a chi-square test statistic of 8.56. At = .05 and = 3, the critical value of the chi-square
statistic is 7.81. What is the appropriate statistical conclusion?
a.
Reject the null hypothesis
b.
Can't determine; not enough information given
c.
Fail to reject the null hypothesis
d.
Reject the alternative hypothesis
e.
Conclude that the null hypothesis is true
a
The appropriate conclusion is to reject the null hypothesis. See 17-4: Testing
Hypotheses About Individual Variables.
1
Easy
Understand
Multiple Choice
False
17.05 - Overview the basic purpose of hypothesis testing.
7/31/2017 6:48 AM
7/31/2017 7:03 AM
22. A researcher had calculated the sample chi-square test statistic to be equal to |2 = 7.71. For an alpha level of 0.10 and
4 degrees of freedom, the critical value of the chi-square statistic is 7.78. The appropriate conclusion is that the
a.
sample result is likely to be attributed to chance alone.
b.
null hypothesis should not be rejected.
c.
null hypothesis should be rejected.
d.
Both a and b are correct.
e.
The alternative hypothesis is true.
d
The appropriate conclusion is that the sample result is likely to be attributed to
chance alone, and the null hypothesis should not be rejected. See 17-4: Testing
Hypotheses About Individual Variables.
1
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Page 10
Easy
Understand
Multiple Choice
False
17.05 - Overview the basic purpose of hypothesis testing.
7/31/2017 7:04 AM
7/31/2017 7:06 AM
23. A clothing manufacturer traditionally makes sweatshirts from three different fabrics: A, B and C. Over the years, the
percentages sold of each fabric were 50, 35, and 15, respectively. Recently, the manufacturer began producing running
suits from the same three fabrics. During the first three months of production, the company received orders for 6,500 suits
made from fabric A, 3,400 from fabric B, and 2,700 from fabric C. What would be the expected number of running suits
made of fabric B sold during the first three months based on past years' sales results of sweatshirts?
a.
3,500
b.
1,190
c.
4,410
d.
4,500
e.
None of these are correct.
c
The expected number would be 4,410. See 17-4: Testing Hypotheses About
Individual Variables.
1
Easy
Apply
Multiple Choice
False
17.05 - Overview the basic purpose of hypothesis testing.
7/31/2017 7:09 AM
7/31/2017 7:10 AM
24. A clothing manufacturer traditionally makes sweatshirts from three different fabrics: A, B and C. Over the years, the
percentages sold of each fabric were 50, 35, and 15, respectively. Recently, the manufacturer began producing running
suits from the same three fabrics. During the first three months of production, the company received orders for 6,500 suits
made from fabric A, 3,400 from fabric B, and 2,700 from fabric C. What is the appropriate test to determine whether sales
results of the new running suit are similar to what would be expected given the previous sales history of sweatshirts made
of the three fabrics?
a.
Regression analysis
b.
z-test for comparing sample mean against a standard
c.
Chi-square test
d.
z-test for comparing sample proportion against a standard
e.
None of these are correct.
c
The chi-square test would be appropriate. See 17-4: Testing Hypotheses About
Individual Variables.
1
Easy
Apply
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Page 11
Multiple Choice
False
17.05 - Overview the basic purpose of hypothesis testing.
7/31/2017 7:12 AM
7/31/2017 7:15 AM
25. A clothing manufacturer traditionally makes sweatshirts from three different fabrics: A, B and C. Over the years, the
percentages sold of each fabric were 50, 35, and 15, respectively. Recently, the manufacturer began producing running
suits from the same three fabrics. During the first three months of production, the company received orders for 6,500 suits
made from fabric A, 3,400 from fabric B, and 2,700 from fabric C. What is the value of the test statistic useful for
determining how well the pattern of sales (by fabric type) of the new running suit corresponds to the expected pattern?
a.
136.21
b.
584.81
c.
0.973
d.
422.13
e.
None of these are correct.
b
The value of the test statistic would be 584.81. See 17-4: Testing Hypotheses
About Individual Variables.
1
Easy
Apply
Multiple Choice
False
17.05 - Overview the basic purpose of hypothesis testing.
7/31/2017 7:20 AM
9/21/2017 11:15 AM
26. The confidence interval is
a.
a measure of the variation in responses for continuous measures.
b.
the level of error related to the probability of rejecting the null hypothesis.
c.
a counting of the number of cases that fall into the various response categories.
d.
a projection of the range within which a population parameter will lie at a given level of confidence based on a
statistic obtained from an appropriately drawn sample.
e.
the arithmetic mean value across all responses for a variable.
ANSWER:
d
RATIONALE:
The confidence interval is a projection of the range within which a population parameter
will lie at a given level of confidence based on a statistic obtained from an appropriately
drawn sample. See 17-2: Basic Univariate Statistics: Continuous Measures.
POINTS:
1
DIFFICULTY:
Easy
REFERENCES:
Remember
QUESTION TYPE:
Multiple Choice
HAS VARIABLES:
False
DATE CREATED:
7/31/2017 7:26 AM
DATE MODIFIED:
7/31/2017 7:28 AM
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Page 12
27. The population mean is hypothesized to be 200. The sample mean (x-bar) is 220. The sample size (n) is 25. The
sample standard deviation (s) is 15. The estimated value of the standard error of the mean is
a.
2.6.
b.
3.0.
c.
1.6.
d.
0.6.
e.
0.9.
e
The estimated value of the standard error of the mean is 0.9. See 17-2: Basic
Univariate Statistics: Continuous Measures.
1
Easy
Apply
Multiple Choice
False
17.04 - Discuss confidence intervals for proportions and means.
7/31/2017 7:31 AM
7/31/2017 7:32 AM
28. The population mean is hypothesized to be 200. The sample mean (x-bar) is 220. The sample size (n) is 25. The
sample standard deviation (s) is 15. The median split for this sample is
a.
100.
b.
110.
c.
200.
d.
220.
e.
There is not enough information to determine the median split.
e
There is not enough information to determine the median split. See 17-2: Basic
Univariate Statistics: Continuous Measures.
1
Easy
Apply
Multiple Choice
False
17.04 - Discuss confidence intervals for proportions and means.
7/31/2017 7:41 AM
7/31/2017 7:42 AM
29. The population mean is hypothesized to be 200. The sample mean (x-bar) is 220. The sample size (n) is 25. The
sample standard deviation (s) is 15. The degrees of freedom would equal
a.
14.
b.
24.
c.
219.
d.
199.
e.
Cannot tell from the given information
b
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Page 13
The degrees of freedom would equal 24. See 17-2: Basic Univariate Statistics:
Continuous Measures.
1
Easy
Apply
Multiple Choice
False
17.04 - Discuss confidence intervals for proportions and means.
7/31/2017 7:45 AM
7/31/2017 7:47 AM
30. Which of the following statements about mean values is NOT true?
a.
Mean values can be calculated for any variable in a data set.
b.
Mean values are only meaningful for continuous measures.
c.
Mean values should be presented with several decimals to improve their precision.
d.
The mean is only useful with equal-interval scales.
e.
Outliers can have a very strong influence on a sample mean.
c
All of the statements are true except that mean values should be presented with
several decimals to improve their precision. See 17-2: Basic Univariate Statistics:
Continuous Measures.
1
Easy
Understand
Multiple Choice
False
17.04 - Discuss confidence intervals for proportions and means.
7/31/2017 7:50 AM
7/31/2017 7:56 AM
31. Which of the following statements is TRUE with respect to outliers?
a.
They represent special cases that should be treated differently from the rest of the observations.
b.
They can be located using frequency analysis.
c.
They can have a very strong influence on the sample mean.
d.
All of these are correct.
e.
None of these are correct.
d
All of these are true. See 17-2: Basic Univariate Statistics: Continuous Measures.
1
Easy
Remember
Multiple Choice
False
17.04 - Discuss confidence intervals for proportions and means.
7/31/2017 8:01 AM
9/21/2017 11:15 AM
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Page 14
32. When it comes to standard deviations, if everyone were basically the same on some characteristic or felt the same way
about some topic or object, the standard deviation would be
a.
very small.
b.
difficult, if not impossible, to calculate.
c.
very large.
d.
None of these are correct.
e.
very small and difficult to calculate.
a
The standard deviation would be very small. See 17-2: Basic Univariate Statistics:
Continuous Measures.
1
Easy
Remember
Multiple Choice
False
17.04 - Discuss confidence intervals for proportions and means.
7/31/2017 8:05 AM
9/21/2017 11:16 AM
33. Converting from continuous to categorical measures
a.
results in loss of information about a variable.
b.
works because higher levels of measurement have all the properties of lower levels of measurement.
c.
in many cases is really useful for interpreting the results.
d.
is a process that really isn't subject to a lot of rules.
e.
All of these are correct.
e
All of these are correct. See 17-2: Basic Univariate Statistics: Continuous
Measures.
1
Easy
Remember
Multiple Choice
False
17.04 - Discuss confidence intervals for proportions and means.
7/31/2017 8:10 AM
7/31/2017 8:14 AM
34. Which of the following is FALSE about the use of percentages when reporting results?
a.
Unless decimals have a special purpose, they should be omitted.
b.
Percentages should be rounded to whole numbers.
c.
Decimals may convey greater accuracy than the figures can support.
d.
It is unnecessary and redundant to include percentages along with the raw count for frequency analyses.
e.
All of these statements are true concerning the use of percentages when reporting results.
d
All of the statements are true except that it is unnecessary and redundant to

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