# Marketing Chapter 18 Date Created Date Modified Multiple Regression Analysis Useful When There Are Independent

Document Type
Test Prep
Book Title
Basic Marketing Research 9th Edition
Authors
Gilbert A. Churchill, Tom J. Brown, Tracy A. Suter
Page 17
and a paired sample t-test for means.
DATE CREATED:
7/31/2017 8:23 AM
DATE MODIFIED:
7/31/2017 8:25 AM
38. A research study involving the research question: "On the basis of a survey of husband-wife house-holds, is there a
significant difference between the mean attitude score of husbands and that of wives toward our product?" will involve
a test
a.
for a single proportion.
b.
of two means when samples are independent.
c.
for a single mean.
d.
of two means when samples are dependent.
e.
None of these are correct.
d
RATIONALE:
This will involve a test of two means when samples are dependent. See 18-3:
Paired Sample T-Test for Means.
POINTS:
1
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Easy
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LEARNING OBJECTIVES:
18.04 - Explain the difference between an independent sample t-test for means
and a paired sample t-test for means.
DATE CREATED:
7/31/2017 8:28 AM
DATE MODIFIED:
7/31/2017 8:29 AM
39. If a = 0.152 and b = 1.32, the simple regression equation is
a.
Yi = 1.32 0.152 Xi
b.
Yi = 0.152 + 1.32 Xi
c.
Yi = 0.152 1.32 Xi
d.
Yi = 0.152/1.32 + Xi
e.
None of these are correct.
b
RATIONALE:
Yi = 0.152 + 1.32 Xi. See 18-5: Regression Analysis.
POINTS:
1
DIFFICULTY:
Easy
REFERENCES:
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False
LEARNING OBJECTIVES:
18.06 - Discuss a technique for examining the influence of one or more predictor
variables on an outcome variable.
DATE CREATED:
7/31/2017 8:32 AM
DATE MODIFIED:
7/31/2017 8:35 AM
40. Which statistical technique should you use when you are attempting to answer the question: "Is there a significant
relationship between the customers' disposable income (measured in dollars) and their repeat-buying behavior
(measured by the number of rebuys in a twelve-month period)?"
Page 18
a.
b.
c.
d.
e.
d
RATIONALE:
The Pearson correlation coefficient is the appropriate technique. See 18-4:
Pearson Product-Moment Correlation Coefficient.
POINTS:
1
DIFFICULTY:
Easy
REFERENCES:
Understand
QUESTION TYPE:
Multiple Choice
HAS VARIABLES:
False
LEARNING OBJECTIVES:
18.05 - Discuss the Pearson product-moment correlation coefficient.
DATE CREATED:
7/31/2017 8:37 AM
DATE MODIFIED:
7/31/2017 8:39 AM
41. Which of the following statements about the interpretation of correlations is NOT true?
a.
Just because two variables are correlated doesn't mean that one necessarily caused the other.
b.
There is nothing in correlation analysis that can be used to establish causality.
c.
When you obtain a statistically significant correlation coefficient between two variables, you can safely
assume that one variable caused another.
d.
All that analytical procedures can do is measure the nature and degree of association between variables.
e.
Statements of causality must come from underlying knowledge and theories about the phenomena under
investigation.
c
RATIONALE:
All of these are true except that when you obtain a statistically significant
correlation coefficient between two variables, you can safely assume that one
variable caused another. See 18-5: Regression Analysis.
POINTS:
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18.06 - Discuss a technique for examining the influence of one or more predictor
variables on an outcome variable.
DATE CREATED:
7/31/2017 8:42 AM
DATE MODIFIED:
7/31/2017 8:44 AM
42. Multiple regression analysis is useful when there are ____ independent variable(s) and ____ dependent variable(s).
a.
more than one, one
b.
one, more than one
c.
more than one, more than one
d.
one, one
e.
None of these are correct.
Page 19
a
RATIONALE:
Multiple regression analysis is useful when there are more than one independent
variable(s) and one dependent variable(s). See 18-5: Regression Analysis.
POINTS:
1
DIFFICULTY:
Easy
REFERENCES:
Remember
QUESTION TYPE:
Multiple Choice
HAS VARIABLES:
False
LEARNING OBJECTIVES:
18.06 - Discuss a technique for examining the influence of one or more predictor
variables on an outcome variable.
DATE CREATED:
7/31/2017 8:46 AM
DATE MODIFIED:
7/31/2017 8:48 AM
43. In which of the following situations would it be useful to test for differences between two groups?
a.
A retailer wishes to know if customer satisfaction is different between in-store vs. online shoppers.
b.
A beverage company wants to know if a new beverage concept differs between users vs. nonusers of the
current brand.
c.
A department store wishes to know the differences between online catalogs vs. mail order catalog shoppers.
d.
A state university wants to know is there is a significant difference in GPA between undergradu-ate and
e.
All of these situations would benefit from tests for differences between two groups.
e
RATIONALE:
All of these would benefit. See 18-3: Paired Sample T-Test for Means.
POINTS:
1
DIFFICULTY:
Easy
REFERENCES:
Understand
QUESTION TYPE:
Multiple Choice
HAS VARIABLES:
False
LEARNING OBJECTIVES:
18.04 - Explain the difference between an independent sample t-test for means
and a paired sample t-test for means.
DATE CREATED:
7/31/2017 8:51 AM
DATE MODIFIED:
7/31/2017 8:53 AM
44. When a computed z-value (for a test for differences between two percentages), say 4.51, is larger than the standard
z-value, say 1.96, then this amounts to
a.
support for the null hypothesis; the two percentages are different.
b.
no support for the null hypothesis; the two percentages are not different.
c.
support for the null hypothesis; the two percentages is not different.
d.
no support for the null hypothesis; the two percentages are different.
e.
None of these are correct.
d
RATIONALE:
This amounts to no support for the null hypothesis; the two percentages are
different. See 18-1: Cross Tabulation.
POINTS:
1
DIFFICULTY:
Easy
REFERENCES:
Understand
Page 20
QUESTION TYPE:
Multiple Choice
HAS VARIABLES:
False
LEARNING OBJECTIVES:
18.02 - Explain the purpose and importance of cross tabulation.
DATE CREATED:
7/31/2017 8:55 AM
DATE MODIFIED:
7/31/2017 8:57 AM
45. Let's assume there are sophomores, juniors, and seniors in your marketing research class and we want to know if
their average GPAs differ. What is the proper statistical test?
a.
t-test
b.
z-test
c.
Chi-square test
d.
Analysis of variance (ANOVA)
e.
None of these are correct.
d
RATIONALE:
The proper statistical method is ANOVA. See 18-5: Regression Analysis.
POINTS:
1
DIFFICULTY:
Easy
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18.06 - Discuss a technique for examining the influence of one or more predictor
variables on an outcome variable.
DATE CREATED:
7/31/2017 9:00 AM
DATE MODIFIED:
7/31/2017 9:04 AM
46. Regression analysis
a.
is a means for getting at the nature of the relationship between one or more predictor variables and an
outcome variable.
b.
"regresses" the independent variable on the set of outcome variables.
c.
produces regression coefficients for each of the predictor variables.
d.
All of these are correct.
e.
is a means for getting at the nature of the relationship between one or more predictor variables and an
outcome variable and produces regression coefficients for each of the predictor variables.
e
RATIONALE:
Regression analysis is a means for getting at the nature of the relationship
between one or more predictor variables and an outcome variable and produces
regression coefficient for each of the predictor variables. See 18-5: Regression
Analysis.
POINTS:
1
DIFFICULTY:
Easy
REFERENCES:
Understand
QUESTION TYPE:
Multiple Choice
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False
LEARNING OBJECTIVES:
18.06 - Discuss a technique for examining the influence of one or more predictor
variables on an outcome variable.
DATE CREATED:
7/31/2017 9:05 AM
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DATE MODIFIED:
9/21/2017 11:25 AM
47. What should be done before trying to interpret individual regression coefficients?
a.
See whether there is an overall statistically significant relationship between the set of predictors and the
outcome variable.
b.
Verify that the set of predictors can explain a meaningful portion of the variation in the outcome variable.
c.
Calculate the coefficient of multiple determination, or coefficient of determination, whichever is appropriate.
d.
All of these are correct.
e.
None of these are correct.
d
RATIONALE:
Calculate the coefficient of multiple determination, or coefficient of determination,
whichever is appropriate. See 18-5: Regression Analysis.
POINTS:
1
DIFFICULTY:
Easy
REFERENCES:
Understand
QUESTION TYPE:
Multiple Choice
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False
LEARNING OBJECTIVES:
18.06 - Discuss a technique for examining the influence of one or more predictor
variables on an outcome variable.
DATE CREATED:
7/31/2017 9:12 AM
DATE MODIFIED:
9/21/2017 11:26 AM
48. If we were comparing the difference between the mean number of sports drinks consumed by male vs. female
athletes during a typical week, and we calculated a z value of 4.33, we would conclude that the probability of support of
the
a.
null hypothesis of no difference is less than < 0.01 because 4.33 is greater than 2.58.
b.
alternative hypothesis of no difference is less than < 0.01 because 4.33 is greater than 2.58.
c.
null hypothesis of no difference is less than < 0.01 because 4.33 is less than 2.58.
d.
alternative hypothesis of no difference is less than < 0.01 because 4.33 is less than 2.58.
e.
None of these are correct.
a
RATIONALE:
The probability of support of the null hypothesis of no difference is less than < 0.01
because 4.33 is greater than 2.58. See 18-1: Cross Tabulation.
POINTS:
1
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Easy
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18.02 - Explain the purpose and importance of cross tabulation.
DATE CREATED:
7/31/2017 9:17 AM
DATE MODIFIED:
7/31/2017 9:19 AM
49. Suppose you were given an example of running a chi-square test using SPSS. The output shows a "Pearson Chi-
Square" value of 82.123, df = 3 and the Asymp. Sig. = 0.000. This means
a.
there is a significant association.
b.
there is no significant association.
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c.
the difference is associative.
d.
the means are not equal.
e.
the variances are equal.
a
RATIONALE:
There is a significant association. See 18-1: Cross Tabulation.
POINTS:
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18.02 - Explain the purpose and importance of cross tabulation.
DATE CREATED:
7/31/2017 9:22 AM
DATE MODIFIED:
7/31/2017 9:24 AM
50. Assume that a researcher determines that a p-value of 0.01 or below determines significance. Listed below are
several correlation coefficients and their respective significance levels. Which correlation coefficient demonstrates an
association not likely due to chance (i.e., significant)?
a.
0.22, 0.06
b.
0.75, 0.00
c.
0.32, 0.15
d.
0.76, 0.95
e.
0.26, 0.10
b
RATIONALE:
0.75, 0.00 is an association. See 18-5: Regression Analysis.
POINTS:
1
DIFFICULTY:
Easy
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False
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18.06 - Discuss a technique for examining the influence of one or more predictor
variables on an outcome variable.
DATE CREATED:
7/31/2017 9:27 AM
DATE MODIFIED:
7/31/2017 9:29 AM
51. Let's assume we find in a study that the Pearson's correlation coefficient between number of years of education and
cigarette smoking is 0.73. This means that as education level increases,
a.
smoking tends to increase.
b.
smoking tends to decrease.
c.
smoking changes 73%.
d.
Education and smoking are unrelated.
e.
An educated person smokes 73 cigarettes a day.
b
RATIONALE:
As education level increases, smoking tends to decrease. See 18-4: Pearson
Product-Moment Correlation Coefficient.
POINTS:
1
Page 23
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18.05 - Discuss the Pearson product-moment correlation coefficient.
DATE CREATED:
7/31/2017 9:32 AM
DATE MODIFIED:
7/31/2017 9:35 AM
52. The NFL office discovered data covering attendance at professional football games in the late 1940s and early 1950s.
The game with the highest attendance was between the St. Louis Cardinals and the New York Giants. The office also
found considerable information that someone had collected on each game day such as the level of GDP, the Dow,
number of persons employed, number of new businesses formed during the week preceding the game, and the
population. A student intern took the information and built a regression model to predict game attendance for the
upcoming season. The model should
a.
accurately predict game attendance.
b.
NOT predict game attendance accurately because the variable levels of today (i.e., population, Dow, etc.) are
out of range of those used to build the regression model.
c.
predict game attendance accurately because the variable levels of today (i.e., population, Dow, etc.) are out
of range of those used to build the regression model.
d.
predict game attendance accurately because the variable levels (i.e., population, Dow, etc.) are within range
of those used to build the regression model.
e.
None of these are correct.
b
RATIONALE:
The model should not predict game attendance accurately because the variable
levels of today (i.e., population, Dow, etc.) are out of range of those used to build
the regression model. See 18-5: Regression Analysis.
POINTS:
1
DIFFICULTY:
Easy
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False
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18.06 - Discuss a technique for examining the influence of one or more predictor
variables on an outcome variable.
DATE CREATED:
7/31/2017 9:38 AM
DATE MODIFIED:
7/31/2017 9:42 AM
53. If the F-value in ANOVA produces a significantly high p-value (a.k.a. "Sig." in SPSS) of 0.11 or more, then it is
appropriate to proceed with a post-hoc test (e.g., Duncan).
a.
True
b.
False
False
POINTS:
1
DIFFICULTY:
Easy
REFERENCES:
Understand
QUESTION TYPE:
True / False
HAS VARIABLES:
False
LEARNING OBJECTIVES:
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Page 24
variables on an outcome variable.
DATE CREATED:
7/31/2017 9:45 AM
DATE MODIFIED:
7/31/2017 9:48 AM
54. In the chi-square analysis, the greater the differences between the observed frequencies and the expected
frequencies, the less likely it is that there will be a statistically significant relationship.
a.
True
b.
False
False
POINTS:
1
DIFFICULTY:
Easy
REFERENCES:
Understand
QUESTION TYPE:
True / False
HAS VARIABLES:
False
LEARNING OBJECTIVES:
18.02 - Explain the purpose and importance of cross tabulation.
DATE CREATED:
7/31/2017 9:52 AM
DATE MODIFIED:
7/31/2017 9:53 AM
55. If you have a significant and very strong (e.g., > 0.90) correlation coefficient, you may assume there is a causal
relationship between the two variables.
a.
True
b.
False
False
POINTS:
1
DIFFICULTY:
Easy
REFERENCES:
Understand
QUESTION TYPE:
True / False
HAS VARIABLES:
False
LEARNING OBJECTIVES:
18.05 - Discuss the Pearson product-moment correlation coefficient.
DATE CREATED:
7/31/2017 9:56 AM
DATE MODIFIED:
7/31/2017 9:57 AM
56. The manager of the New England Patriots conducted a large survey. He wanted to know if there was an association
between fans being "season ticket holders" vs. "non-season ticket holders" and whether they "bought" vs. "didn't buy"
team merchandise at the game. Because his survey included these measurements, he used SPSS to run a Pearson
correlation coefficient that turned out to be 0.88 with a Sig. value of .001. This meant there is a significant relationship.
a.
True
b.
False
False
POINTS:
1
DIFFICULTY:
Easy
REFERENCES:
Understand
QUESTION TYPE:
True / False
HAS VARIABLES:
False
LEARNING OBJECTIVES:
18.05 - Discuss the Pearson product-moment correlation coefficient.
DATE CREATED:
7/31/2017 10:00 AM
Page 25
DATE MODIFIED:
7/31/2017 10:01 AM
57. Olive Garden restaurants know that customers drink beverages for lunch and alcoholic drinks at supper. This is an
example of an associative type of relationship.
a.
True
b.
False
True
POINTS:
1
DIFFICULTY:
Easy
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Understand
QUESTION TYPE:
True / False
HAS VARIABLES:
False
LEARNING OBJECTIVES:
18.06 - Discuss a technique for examining the influence of one or more predictor
variables on an outcome variable.
DATE CREATED:
7/31/2017 10:04 AM
DATE MODIFIED:
7/31/2017 10:05 AM
58. Carters, a marketer of children apparel, knows that as girls increase in age, their dress size tends to get larger. This is
an example of a causal type of relationship.
a.
True
b.
False
False
POINTS:
1
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Easy
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QUESTION TYPE:
True / False
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False
LEARNING OBJECTIVES:
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variables on an outcome variable.
DATE CREATED:
7/31/2017 10:08 AM
DATE MODIFIED:
7/31/2017 10:09 AM
59. The multiple R, also called the coefficient of determination, in multiple regression ranges from 0.00 to +1.00 and
represents the amount of the dependent variable "explained" by the combined independent variables.
a.
True
b.
False
True
POINTS:
1
DIFFICULTY:
Easy
REFERENCES:
Understand
QUESTION TYPE:
True / False
HAS VARIABLES:
False
LEARNING OBJECTIVES:
18.06 - Discuss a technique for examining the influence of one or more predictor
variables on an outcome variable.
DATE CREATED:
7/31/2017 10:13 AM
DATE MODIFIED:
7/31/2017 10:14 AM
Page 26
60. In multiple regression analysis, t tests are used to test for the statistical significance of betas. If a beta is insignificant,
it means that its respective independent variable plays no meaningful role in predicting the dependent variable, and the
independent variable should be "removed" from the model.
a.
True
b.
False
True
POINTS:
1
DIFFICULTY:
Easy
REFERENCES:
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True / False
HAS VARIABLES:
False
LEARNING OBJECTIVES:
18.06 - Discuss a technique for examining the influence of one or more predictor
variables on an outcome variable.
DATE CREATED:
7/31/2017 10:17 AM
DATE MODIFIED:
7/31/2017 10:18 AM
61. The simple regression technique in SPSS, not the researcher, specifies which variable should be the independent
variable and which one should be the dependent variable.
a.
True
b.
False
False
POINTS:
1
DIFFICULTY:
Easy
REFERENCES:
Understand
QUESTION TYPE:
True / False
HAS VARIABLES:
False
LEARNING OBJECTIVES:
18.06 - Discuss a technique for examining the influence of one or more predictor
variables on an outcome variable.
DATE CREATED:
7/31/2017 10:21 AM
DATE MODIFIED:
7/31/2017 10:22 AM
62. In a regression analysis, determining the statistical significance of the slope involves the use of the t-statistic.
a.
True
b.
False
True
POINTS:
1
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True / False
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False
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variables on an outcome variable.
DATE CREATED:
7/31/2017 10:26 AM
DATE MODIFIED:
7/31/2017 10:27 AM
63. The magnitude of the Pearson correlation coefficient indicates the direction of association, while its sign indicates
the strength of the association.
Page 27
a.
True
b.
False
False
POINTS:
1
DIFFICULTY:
Easy
REFERENCES:
Understand
QUESTION TYPE:
True / False
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False
LEARNING OBJECTIVES:
18.05 - Discuss the Pearson product-moment correlation coefficient.
DATE CREATED:
7/31/2017 10:30 AM
DATE MODIFIED:
7/31/2017 10:33 AM
64. All other variables held constant, a 95% confidence interval will give us a narrower range than will a 99% confidence
interval.
a.
True
b.
False
False
POINTS:
1
DIFFICULTY:
Easy
REFERENCES:
Understand
QUESTION TYPE:
True / False
HAS VARIABLES:
False
LEARNING OBJECTIVES:
18.04 - Explain the difference between an independent sample t-test for means
and a paired sample t-test for means.
DATE CREATED:
7/31/2017 10:36 AM
DATE MODIFIED:
7/31/2017 10:38 AM
65. A toy storeowner hypothesizes, at the 95% level of confidence, that parents spend less than \$100 on toys per visit to
her store. A sample is taken, and the hypothesis test shows a z value of −1.65. We accept the hypothesis.
a.
True
b.
False
True
POINTS:
1
DIFFICULTY:
Easy
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Understand
QUESTION TYPE:
True / False
HAS VARIABLES:
False
LEARNING OBJECTIVES:
18.04 - Explain the difference between an independent sample t-test for means
and a paired sample t-test for means.
DATE CREATED:
7/31/2017 10:41 AM
DATE MODIFIED:
7/31/2017 10:43 AM
66. A statistic used to measure the strength of relationship between categorical variables is called a Cramer's V.
a.
True
b.
False
True
Page 28
POINTS:
1
DIFFICULTY:
Easy
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QUESTION TYPE:
True / False
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False
LEARNING OBJECTIVES:
18.02 - Explain the purpose and importance of cross tabulation.
DATE CREATED:
7/31/2017 10:52 AM
DATE MODIFIED:
7/31/2017 10:53 AM
67. Correlation analysis, along with other mathematical procedures, can be used to establish causality.
a.
True
b.
False
False
POINTS:
1
DIFFICULTY:
Easy
REFERENCES:
Understand
QUESTION TYPE:
True / False
HAS VARIABLES:
False
LEARNING OBJECTIVES:
18.06 - Discuss a technique for examining the influence of one or more predictor
variables on an outcome variable.
DATE CREATED:
7/31/2017 10:54 AM
DATE MODIFIED:
7/31/2017 10:54 AM
68. Cross tabulation works equally well with continuous measures that have been recast as categorical measures.
a.
True
b.
False
True
POINTS:
1
DIFFICULTY:
Easy
REFERENCES:
Understand
QUESTION TYPE:
True / False
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False
LEARNING OBJECTIVES:
18.02 - Explain the purpose and importance of cross tabulation.
DATE CREATED:
7/31/2017 10:55 AM
DATE MODIFIED:
7/31/2017 10:55 AM
69. The error term in the regression model represents all factors that determine the criterion variables that are not part
of the model.
a.
True
b.
False
True
POINTS:
1
DIFFICULTY:
Easy
REFERENCES:
Understand
QUESTION TYPE:
True / False
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False
Page 29
LEARNING OBJECTIVES:
18.06 - Discuss a technique for examining the influence of one or more predictor
variables on an outcome variable.
DATE CREATED:
7/31/2017 10:56 AM
DATE MODIFIED:
7/31/2017 10:56 AM
70. Percentages are always calculated in the direction of the causal variable.
a.
True
b.
False
True
POINTS:
1
DIFFICULTY:
Easy
REFERENCES:
Understand
QUESTION TYPE:
True / False
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False
LEARNING OBJECTIVES:
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variables on an outcome variable.
DATE CREATED:
7/31/2017 10:57 AM
DATE MODIFIED:
7/31/2017 10:57 AM
71. The coefficient of determination represents the relative proportion of the total variation in the outcome variable
that can be accounted for by the predictor variable in the regression.
a.
True
b.
False
True
POINTS:
1
DIFFICULTY:
Easy
REFERENCES:
Understand
QUESTION TYPE:
True / False
HAS VARIABLES:
False
LEARNING OBJECTIVES:
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variables on an outcome variable.
DATE CREATED:
7/31/2017 10:59 AM
DATE MODIFIED:
7/31/2017 10:59 AM
72. A factorial design is an ANOVA analysis that includes two or more dependent variables.
a.
True
b.
False
False
POINTS:
1
DIFFICULTY:
Easy
REFERENCES:
Understand
QUESTION TYPE:
True / False
HAS VARIABLES:
False
LEARNING OBJECTIVES:
18.06 - Discuss a technique for examining the influence of one or more predictor
variables on an outcome variable.
DATE CREATED:
7/31/2017 11:00 AM
Page 30
DATE MODIFIED:
7/31/2017 11:00 AM
73. A simple regression is a statistical technique used to derive an equation that relates a single continuous dependent
variable to two or more independent variables.
a.
True
b.
False
False
POINTS:
1
DIFFICULTY:
Easy
REFERENCES:
Understand
QUESTION TYPE:
True / False
HAS VARIABLES:
False
LEARNING OBJECTIVES:
18.06 - Discuss a technique for examining the influence of one or more predictor
variables on an outcome variable.
DATE CREATED:
7/31/2017 11:01 AM
DATE MODIFIED:
7/31/2017 11:01 AM
74. A statistical technique used with a continuous dependent variable and one or more categorical independent
variables is called a Cramer V.
a.
True
b.
False
False
POINTS:
1
DIFFICULTY:
Easy
REFERENCES:
Understand
QUESTION TYPE:
True / False
HAS VARIABLES:
False
LEARNING OBJECTIVES:
18.06 - Discuss a technique for examining the influence of one or more predictor
variables on an outcome variable.
DATE CREATED:
7/31/2017 11:02 AM
DATE MODIFIED:
7/31/2017 11:02 AM
75. While the chi-square test indicates whether two variables are independent, it doesn't measure the strength of
association when they are dependent.
a.
True
b.
False
True
POINTS:
1
DIFFICULTY:
Easy
REFERENCES:
Understand
QUESTION TYPE:
True / False
HAS VARIABLES:
False
LEARNING OBJECTIVES:
18.02 - Explain the purpose and importance of cross tabulation.
DATE CREATED:
7/31/2017 11:03 AM
DATE MODIFIED:
7/31/2017 11:03 AM
Page 31
76. A statistic used to measure the strength of relationship between categorical variables is called a regression analysis.
a.
True
b.
False
False
POINTS:
1
DIFFICULTY:
Easy
REFERENCES:
Understand
QUESTION TYPE:
True / False
HAS VARIABLES:
False
LEARNING OBJECTIVES:
18.02 - Explain the purpose and importance of cross tabulation.
DATE CREATED:
7/31/2017 11:04 AM
DATE MODIFIED:
7/31/2017 11:04 AM
77. The independent samples t-test for means always compares mean scores for the same variable measured in two
groups.
a.
True
b.
False
True
POINTS:
1
DIFFICULTY:
Easy
REFERENCES:
Understand
QUESTION TYPE:
True / False
HAS VARIABLES:
False
LEARNING OBJECTIVES:
18.04 - Explain the difference between an independent sample t-test for means
and a paired sample t-test for means.
DATE CREATED:
7/31/2017 11:05 AM
DATE MODIFIED:
7/31/2017 11:05 AM
78. Regression is a robust analytical tool that can also be used when one or more dependent variables are categorical as
opposed to continuous variables.
a.
True
b.
False
False
POINTS:
1
DIFFICULTY:
Easy
REFERENCES:
Understand
QUESTION TYPE:
True / False
HAS VARIABLES:
False
LEARNING OBJECTIVES:
18.06 - Discuss a technique for examining the influence of one or more predictor
variables on an outcome variable.
DATE CREATED:
7/31/2017 11:06 AM
DATE MODIFIED:
7/31/2017 11:07 AM
79. Multiple regression is used to derive an equation that relates a single continuous dependent variable to two or more
independent variables.
a.
True
Page 32
b.
False
True
POINTS:
1
DIFFICULTY:
Easy
REFERENCES:
Understand
QUESTION TYPE:
True / False
HAS VARIABLES:
False
LEARNING OBJECTIVES:
18.06 - Discuss a technique for examining the influence of one or more predictor
variables on an outcome variable.
DATE CREATED:
7/31/2017 11:07 AM
DATE MODIFIED:
7/31/2017 11:08 AM
80. Regression coefficients represent the average change in the outcome variable per unit change in the associated
predictor variable, holding all other predictor variables constant.
a.
True
b.
False
True
POINTS:
1
DIFFICULTY:
Easy
REFERENCES:
Understand
QUESTION TYPE:
True / False
HAS VARIABLES:
False
LEARNING OBJECTIVES:
18.06 - Discuss a technique for examining the influence of one or more predictor
variables on an outcome variable.
DATE CREATED:
7/31/2017 11:08 AM
DATE MODIFIED:
7/31/2017 11:08 AM
81. Compare and contrast the use of analysis of variance (ANOVA) versus conducting a series of t-tests to examine
differences across groups.
The ANOVA technique (a) would be more efficient, requiring fewer computations, (b)
would decrease the likelihood of rejecting a true null hypothesis, and (c) would consider
the joint effects of different independent variables.
POINTS:
1
DIFFICULTY:
Medium
REFERENCES:
Understand
QUESTION TYPE:
Essay
HAS VARIABLES:
False
LEARNING OBJECTIVES:
18.06 - Discuss a technique for examining the influence of one or more predictor
variables on an outcome variable.
DATE CREATED:
7/31/2017 11:10 AM
DATE MODIFIED:
7/31/2017 11:10 AM

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