Question 1

If the correlation between two variables x and y is equal to −0.90, which of the following is TRUE?

Accepted Answer

A)  x and y are highly related, whereby a positive change in x is accompanied by a positive change in y. 
B)  The two variables x and y are not related to one another. 
C)  x and y are highly related, whereby a negative change in x is accompanied by a positive change in y. 
D)  The coefficient of determination is equal to −0.81. 
E)  An increase in x is accompanied by a decrease in y. 
A)  x and y are highly related, whereby a positive change in x is accompanied by a positive change in y. 
B)  The two variables x and y are not related to one another. 
C)  x and y are highly related, whereby a negative change in x is accompanied by a positive change in y. 
D)  The coefficient of determination is equal to −0.81. 
E)  An increase in x is accompanied by a decrease in y.

Question 2

In which of the following situations would it be useful to test for differences between two groups?

Accepted Answer

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 undergraduate and graduate students. 
E)  All of the above situations would benefit from tests 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 undergraduate and graduate students. 
E)  All of the above situations would benefit from tests for differences between two groups.

Question 3

Which statistical technique should you use to answer the question: "Is there a significant relationship between education level (a four-category ordinal variable) and whether or not consumers are aware that Firestone is a brand of tires?"

Accepted Answer

A)  Multiple regression analysis 
B)  Pearson correlation coefficient 
C)  Chi-square test 
D)  Simple regression analysis 
E)  None of the above. 
A)  Multiple regression analysis 
B)  Pearson correlation coefficient 
C)  Chi-square test 
D)  Simple regression analysis 
E)  None of the above.

Question 4

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.

Accepted Answer

A) True 
 B)False

Question 5

The independent samples t-test for means always compares mean scores for the________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________ variable measured in two groups.

Accepted Answer

The answer of The independent samples t-test for means always...

Question 6

Which of the following statements about the Pearson chi-square test of independence is NOT true?

Accepted Answer

A)  It assesses the degree to which variables in a cross-tabulation are independent of one another. 
B)  The value can range from zero to some upper value limited by sample size and distribution of cases across the cells. 
C)  It doesn't measure the strength of association when variables are dependent. 
D)  It is only useful for univariate analysis. 
E)  All of the above are true. 
A)  It assesses the degree to which variables in a cross-tabulation are independent of one another. 
B)  The value can range from zero to some upper value limited by sample size and distribution of cases across the cells. 
C)  It doesn't measure the strength of association when variables are dependent. 
D)  It is only useful for univariate analysis. 
E)  All of the above are true.

Question 7

Refer to Scenario 18.3. The most appropriate way to calculate percentages in the above table to reflect cause and effect is by dividing

Accepted Answer

A)  each of the entries by 100. 
B)  45 and 55 by 100. 
C)  42 and 58 by 100. 
D)  entries in the first row by 45 and those in the second row by 55. 
E)  entries in the first column by 42 and those in the second column by 58. 
A)  each of the entries by 100. 
B)  45 and 55 by 100. 
C)  42 and 58 by 100. 
D)  entries in the first row by 45 and those in the second row by 55. 
E)  entries in the first column by 42 and those in the second column by 58.

Question 8

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:

Accepted Answer

A) True 
 B)False

Question 9

An analyst has a set of normally distributed intervally scaled data resulting from two observations on the same sample of subjects, and he wishes to investigate if there is any difference in these two means. The appropriate statistical procedure is

Accepted Answer

A)  z-test for difference in two means. 
B)  Analysis of variance (ANOV
A) . 
C)  paired samples t-test. 
D)  chi-square goodness-of-fit test. 
E)  regression analysis. 
A)  z-test for difference in two means. 
B)  Analysis of variance (ANOV
A) . 
C)  paired samples t-test. 
D)  chi-square goodness-of-fit test. 
E)  regression analysis.

Question 10

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

Accepted Answer

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 the above. 
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 the above.

Question 11

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.

Accepted Answer

A) True 
 B)False

Question 12

Consider the regression equation Y = 5 + 16X1 + 38X2 relating annual expenditures on a particular product Y to X1 and X2, where   Which of the following is FALSE? The equation suggests

Accepted Answer

A)  An upper class person could be expected on the average to spend $38 per year more than a lower class person on the product. 
B)  A middle class person could be expected on the average to spend $16 more per year on the product than a lower class person. 
C)  A lower class person could be expected on the average to spend $5 per year on the product. 
D)  An upper class person could be expected on the average to spend $22 more per year on the product than a middle class person. 
E)  An upper class person could be expected on the average to spend $38 per year on the product. 
A)  An upper class person could be expected on the average to spend $38 per year more than a lower class person on the product. 
B)  A middle class person could be expected on the average to spend $16 more per year on the product than a lower class person. 
C)  A lower class person could be expected on the average to spend $5 per year on the product. 
D)  An upper class person could be expected on the average to spend $22 more per year on the product than a middle class person. 
E)  An upper class person could be expected on the average to spend $38 per year on the product.

Question 13

Suppose the ordinary least-squares approach to a regression analysis produced the following Y = 20 - 39X R2 = .90
Which of the following statements is FALSE?

Accepted Answer

A)  For every unit change in X there is a corresponding negative change in the average value of Y of 39 units. 
B)  90 percent of the variation in Y is associated with variation in X. 
C)  The slope of the line is 20. 
D)  The average value of Y given x = 10 is 370. 
E)  If X = 0, then Y = 20. 
A)  For every unit change in X there is a corresponding negative change in the average value of Y of 39 units. 
B)  90 percent of the variation in Y is associated with variation in X. 
C)  The slope of the line is 20. 
D)  The average value of Y given x = 10 is 370. 
E)  If X = 0, then Y = 20.

Question 14

When comparing the independent samples t-test for means and the paired sample t-test for means, one is for

Accepted Answer

A)  univariate analysis while the other is for multivariate analysis. 
B)  small sample sizes while the other is for large sample sizes. 
C)  continuous variables while the other is for categorical variables. 
D)  measures from separate groups while the other is for measures from the same group. 
E)  All of the above. 
A)  univariate analysis while the other is for multivariate analysis. 
B)  small sample sizes while the other is for large sample sizes. 
C)  continuous variables while the other is for categorical variables. 
D)  measures from separate groups while the other is for measures from the same group. 
E)  All of the above.

Question 15

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.

Accepted Answer

A) True 
 B)False

Question 16

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.

Accepted Answer

A) True 
 B)False

Question 17

Refer to Scenario 18.3. In absolute numbers, how many millions of households own a microwave?

Accepted Answer

A)  15 million 
B)  100 million 
C)  42 million 
D)  55 million 
E)  27 million 
A)  15 million 
B)  100 million 
C)  42 million 
D)  55 million 
E)  27 million

Question 18

The manager of 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. Since 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.

Accepted Answer

A) True 
 B)False

Question 19

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)?"

Accepted Answer

A)  Multiple regression analysis 
B)  Chi-Square test 
C)  Simple regression analysis 
D)  Pearson correlation coefficient 
E)  None of the above. 
A)  Multiple regression analysis 
B)  Chi-Square test 
C)  Simple regression analysis 
D)  Pearson correlation coefficient 
E)  None of the above.

Question 20

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

Accepted Answer

A)  there is a significant association. 
B)  there is no significant association. 
C)  the difference is associative. 
D)  the means are not equal. 
E)  the variances are equal. 
A)  there is a significant association. 
B)  there is no significant association. 
C)  the difference is associative. 
D)  the means are not equal. 
E)  the variances are equal.

If the correlation between two variables x and y is equal to −0.90, which of the following is TRUE?

In which of the following situations would it be useful to test for differences between two groups?

Which statistical technique should you use to answer the question: "Is there a significant relationship between education level (a four-category ordinal variable) and whether or not consumers are aware that Firestone is a brand of tires?"

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.

Which of the following statements about the Pearson chi-square test of independence is NOT true?

Refer to Scenario 18.3. The most appropriate way to calculate percentages in the above table to reflect cause and effect is by dividing

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:

An analyst has a set of normally distributed intervally scaled data resulting from two observations on the same sample of subjects, and he wishes to investigate if there is any difference in these two means. The appropriate statistical procedure is

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

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.

Consider the regression equation Y = 5 + 16X₁+ 38X₂relating annual expenditures on a particular product Y to X₁ and X₂, where Which of the following is FALSE? The equation suggests

Suppose the ordinary least-squares approach to a regression analysis produced the following Y = 20 - 39X R²= .90 Which of the following statements is FALSE?

When comparing the independent samples t-test for means and the paired sample t-test for means, one is for

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.

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.

Refer to Scenario 18.3. In absolute numbers, how many millions of households own a microwave?

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)?"

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

The Role of Marketing Research

The Research Process and Ethical Concerns

Problem Formulation

Exploratory Research

Decision Support Systems

Decision Support Systems Working With Big Data

Using External Secondary Data

Conducting Causal Research

Collecting Descriptive Primary Data

Collecting Data by Observation

Collecting Data by Communication

Asking Good Questions

Designing the Data Collection Form

Developing the Sampling Plan

Data Collection Enhancing Response Rates While Limiting Errors

Data Preparation for Analysis

Analysis and Interpretation Individual Variables Independently

The Oral Research Presentation

The Written Research Report

Filters

Exam 18: Analysis and Interpretation Multiple Variables Simultaneously

If the correlation between two variables x and y is equal to −0.90, which of the following is TRUE?

In which of the following situations would it be useful to test for differences between two groups?

Which statistical technique should you use to answer the question: "Is there a significant relationship between education level (a four-category ordinal variable) and whether or not consumers are aware that Firestone is a brand of tires?"

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.

Which of the following statements about the Pearson chi-square test of independence is NOT true?

Refer to Scenario 18.3. The most appropriate way to calculate percentages in the above table to reflect cause and effect is by dividing

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:

An analyst has a set of normally distributed intervally scaled data resulting from two observations on the same sample of subjects, and he wishes to investigate if there is any difference in these two means. The appropriate statistical procedure is

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

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.

Consider the regression equation Y = 5 + 16X1 + 38X2 relating annual expenditures on a particular product Y to X1 and X2, where Which of the following is FALSE? The equation suggests

Suppose the ordinary least-squares approach to a regression analysis produced the following Y = 20 - 39X R2 = .90 Which of the following statements is FALSE?

When comparing the independent samples t-test for means and the paired sample t-test for means, one is for

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.

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.

Refer to Scenario 18.3. In absolute numbers, how many millions of households own a microwave?

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)?"

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

The Role of Marketing Research

The Research Process and Ethical Concerns

Problem Formulation

Exploratory Research

Decision Support Systems

Decision Support Systems Working With Big Data

Using External Secondary Data

Conducting Causal Research

Collecting Descriptive Primary Data

Collecting Data by Observation

Collecting Data by Communication

Asking Good Questions

Designing the Data Collection Form

Developing the Sampling Plan

Data Collection Enhancing Response Rates While Limiting Errors

Data Preparation for Analysis

Analysis and Interpretation Individual Variables Independently

The Oral Research Presentation

The Written Research Report

Filters

Consider the regression equation Y = 5 + 16X₁+ 38X₂relating annual expenditures on a particular product Y to X₁ and X₂, where Which of the following is FALSE? The equation suggests

Suppose the ordinary least-squares approach to a regression analysis produced the following Y = 20 - 39X R²= .90 Which of the following statements is FALSE?