Deck 14: More Powerful Statistical Methods

Question 1

In a regression output in SPSS, R² represents:

A) the independent variable.
B) the dependent variable.
C) the estimated slope of the regression line.
D) the coefficient of determination.

Answer 1

D

Question 2

Bivariate regression can not demonstrate:

A) when the two variables are linear.
B) when the two variables are strongly inversely related.
C) when the two variables are strongly positively related.
D) when the two variables are causally related.

Answer 2

D

Question 3

In a regression equation, sales would typically be the ______________ variable.

A) independent
B) coefficient
C) dependent
D) none of the above

Answer 3

C

Question 4

Researchers use _______________ when their goal is to examine the relationship between two or more predictor variables and on dependent variables.

A) cluster analysis
B) regression analysis
C) correlation analysis
D) conjoint analysis
E) factor analysis

Question 5

What are the possible values in correlation analysis?

A) 0 to 1
B) -1 to +1
C) -1 to 0
D) -.99 to + .99
E) none of the above

Question 6

The dependent variable is also called the __________________.

A) Measure
B) Criterion
C) Principle
D) Standard

Question 7

Which of the following techniques requires that both variables are ratio or interval data?

A) bivariate regression
B) ANOVA
C) t test
D) Pearson's product-moment correlation
E) All are appropriate.

Question 8

An R² of .05 would indicate:

A) a significant relationship between X and Y.
B) a negative relationship between X and Y.
C) a very small relationship between X and Y.
D) none of the above

Question 9

In a regression equation, which symbol represents the dependent variable?

A) Y
B) X
C) e
D) r
E) none of the above

Question 10

_______________ refers to analysis is one of strength of the linear relationship between two variables when one is considered the independent variable and the other the dependent variable

A) Multivariate regression
B) Univariate regression
C) Bivariate regression
D) None of the above

Question 11

___________ are statistical methods of analyzing the relationship between two variables.

A) Bivariate techniques
B) Univariate techniques
C) Multivariate techniques
D) None of the above

Question 12

All of the following are statistical procedures except_______________.

A) Correlation analysis
B) Regression analysis
C) Factor analysis
D) Cohort analysis
E) Factor analysis

Question 13

The percentage of total variation in the dependent variable that is described by the independent variable is expressed by_________.

A) coefficient of determination
B) correlation coefficient
C) coefficient of covariation
D) regression coefficient
E) none of the above

Question 14

If you are studying the impact of training on salesperson performance as indicated on an exam taken by salespersons at the end of training, salesperson sales would be the ____________ variable, and the salesperson exam score would be the _____________ variable.

A) criterion, predictor
B) covariate, independent
C) independent, predictor
D) dependent, independent
E) none of the above

Question 15

The degree to which changes in one variable are associated with changes in another variable.

A) cluster analysis
B) regression analysis
C) correlation analysis
D) conjoint analysis
E) factor analysis

Question 16

When two variables are not correlated at all, the correlation coefficient would be _______.

A) -1
B) 0
C) 1
D) -2
E) none of the above

Question 17

Which of the following are not applications of regression analysis in marketing research:

A) Determining the relative influence of individual satisfaction elements on overall satisfaction
B) Determining which variables are predictive of sales of a particular product or service
C) Estimating the effects of various marketing mix variables on sales or market share
D) Comparing the effect of one variable on another
E) All are applications of regression analysis

Question 18

A correlation analysis between sales and sales training scores results in R = +.98. Which of the following best interprets the relationship between sales and sales training?

A) 98% of the salespeople taking the test have higher sales.
B) The correlation between sales and sales training is very weak and insignificant.
C) The correlation between sales and sales training is strong and positive, indicating that higher sales training scores are closely associated with higher sales and vice-versa.
D) 98% of the variation in sales is explained by variations in sales training scores.
E) none of the above

Question 19

Which of the following is the appropriate technique for correlation analysis, which involves metric (interval or ratio) data?

A) Spearman's rank-order correlation
B) Jensen's analysis of covariance
C) Kendall's coefficient of concordance
D) Pearson's product-moment correlation
E) none of the above

Question 20

____________ is the mathematical technique for fitting a line that best describes the relationship between two variables.

A) Pearson's product-moment correlation
B) Least squares procedure
C) Chi-square test
D) Significance test
E) none of the above

Question 21

The purpose of factor analysis can be best described as:

A) data simplification by summarizing the information contained in a large number of variables into summary measures.
B) presenting the relationship between multiple categorical measures in a low-dimensional diagram.
C) assessing the significance of group differences across many metric dependent variables simultaneously.
D) assessing the degree of correlation of a group of categorical measures.

Question 22

Inference that Coca Cola sales declined when the formula changed is an example of:

A) scaling of coefficients
B) collinearity
C) causation
D) analysis

Question 23

Which of the following would not be an application best suited for multiple regression analysis?

A) estimating the relationship between various demographic and lifestyle variables and the attitude toward a particular product
B) determining which variables best predict the sales of a particular product or service
C) estimating the effect of several marketing mix variables on product sales
D) reducing a large number of potential predictor variables to a smaller set of composite variables

Question 24

If the goal is to classify business travelers into distinct groups based on their responses to 20 questions on preferences to mode of transportation, hotel accommodation, and ethnic food, which of the following techniques would be most appropriate?

A) multiple regression analysis
B) conjoint analysis
C) cluster analysis
D) factor analysis

Question 25

Which of the following techniques is often used for concept testing of new products?

A) conjoint analysis
B) multiple regression analysis
C) perceptual mapping
D) cluster analysis

Question 26

Examining data from a customer survey, the researcher analyzes groups of customers by the number of times they've visited and again by the number of times the customers ate out at all. This is called:

A) factor analysis
B) perceptual mapping
C) cluster analysis
D) conjoint analysis

Question 27

An insurance company wants to know whether the subscribers to its HMO, PPO, or traditional single indemnity plan exhibit better health characteristics. They have the following data for each of their subscribers: % of body weight over optimum weight; blood pressure; cholesterol and hours per week of exercise. The analysis will group subscribers as either healthy, somewhat healthy or not healthy. Which of the following would be the best procedure for making such a determination?

A) factor analysis
B) multiple discriminant analysis
C) multiple regression analysis
D) cluster analysis

Question 28

Summarizing a number of survey questions into a single concept could be achieved with which type of analysis?

A) factor analysis
B) multiple discriminant analysis
C) multiple regression analysis
D) cluster analysis

Question 29

Cluster analysis is particularly valuable for what type of marketing strategy?

A) product differentiation
B) positioning
C) segmentation
D) none of the above

Question 30

One of the key assumptions of regression analysis is that independent variables are_____________________.

A) not correlated
B) linear
C) independent
D) dependent

Question 31

Which of the following is not a step in conjoint analysis?

A) collecting trade-off data
B) estimating factor loadings
C) estimating preference structures
D) predicting consumers' choice

Question 32

This analytical technique helps determine what features a new product or service should have and how it should be priced.

A) factor analysis
B) perceptual mapping
C) multiple discriminant analysis
D) conjoint analysis

Question 33

Suppose an analyst wanted to determine whether or not dollars spent on advertising, number of sales people, number of new products introduced, and dollars spent on research and development were contributing to the growth in company market share. Which of the following procedures would be most appropriate?

A) conjoint analysis
B) cluster analysis
C) multiple regression analysis
D) perceptual mapping

Question 34

The coefficient of determination is normally associated with which of the following multivariate procedures?

A) multiple regression analysis
B) factor analysis
C) conjoint analysis
D) cluster analysis

Question 35

Data mining typically involves four classes of task. Which is not one of the tasks?

A) Clustering
B) Classification
C) Numbering
D) Modeling

Question 36

Which of the following multivariate procedures does not include a dependent variable in its analysis?

A) multiple regression analysis
B) cluster analysis
C) multiple discriminant analysis
D) None of the above procedures includes a dependent variable.

Question 37

______________ is a measure of the percentage of the variation in the dependent variable that is explained by the variation in the independent variables.

A) Discriminant weights
B) Factor loadings
C) Coefficient of determination
D) Coefficient of correlation

Question 38

In factor analysis, the correlation between factor scores and the original variables is known as the factor ________,

A) loading
B) mapping
C) attribute rating
D) conjoint

Question 39

A company that is trying to determine which 3 distinct target markets to focus its marketing efforts on might use which statistical tool?

A) ANOVA
B) multiple regression analysis
C) cluster analysis
D) bivariate regression

Question 40

This procedure is useful for analyzing the relationship among two or more predictor/independent variables and one criterion/dependent variable.

A) multiple discriminant analysis
B) multiple regression analysis
C) conjoint analysis
D) cluster analysis

Question 41

Bivariate regression looks at the relationship between many variables.

Question 42

The R² statistic ranges from -1 to 1.

Question 43

Ordinal data cannot be analyzed using regression analysis.

Question 44

In bivariate regression, both the independent and dependent variables are measured in the form of nominal and/or ordinal data.

Question 45

Data mining is a long-established field of market research.

Question 46

Bivariate statistical techniques are often used to establish cause and effect relationships between two or more variables.

Question 47

Dependent variables are also known as predictor variables.

Question 48

In multiple regression analysis the dependent variable is nominal or categorical.

Question 49

In correlation analysis, the closer the value of R is to -1 or +1, the stronger the correlation between the two variables in question.

Question 50

An R² of 0 indicates no relationship between variables.

Question 51

A perfect correlation indicates that two variables are causally related.

Question 52

The coefficient of correlation R describes the degree of association between X and Y.

Question 53

In the equation for regression analysis, the letter X represents the independent variable.

Question 54

The actual data mining process includes:

A) Clustering
B) Classification
C) Modeling
D) Application
E) all of the above
F) none of the above

Question 55

A R = -.95 is always weaker than +.95, because positive relationships are more significant than negative relationships.

Question 56

If the goal of an analysis is to group respondents into mutually exclusive and collectively exhaustive subgroups, the preferred procedure would be cluster analysis.

Question 57

In the multiple regression formula, which of the following represents the dependent variable?

A) Y
B) a
C) b1
D) X1

Question 58

The coefficient of determination is used in correlation analysis.

Question 59

The task of discovering groups and structures that are similar on certain, selected sets of variables is modeling.

Question 60

Regression techniques analyze relationships between more than 2 variables.

Question 61

Given the Correlation Matrix below, answer questions
Assume that respondents answered the questions with ratio scale responses.
How would you interpret the relationship between Education and Age?

Question 62

Data mining remains an ethically neutral issue.

Question 63

If a company was interested in the impact that advertising and sales price had on sales, cluster analysis would be an appropriate tool to use.

Question 64

Given the Correlation Matrix below, answer questions
Assume that respondents answered the questions with ratio scale responses.
How many pairs of responses were in this correlation analysis? ________

Question 65

In regression analysis, the value of R² is influenced by the number of predictor variables relative to sample size.

Question 66

An analyst will always prefer that the R² be close to zero.

Question 67

Given the Correlation Matrix below, answer questions
Assume that respondents answered the questions with ratio scale responses.
Which of the relationships in the matrix is the strongest?

Question 68

In order to make valid comparisons of regression coefficients, the coefficients must be scaled in the same units, or be standardized.

Question 69

There is no dependent variable in a factor analysis.

Question 70

Interpret the correlation coefficient for the following data:
Sales Sales Training Score
45,000 98
34,500 74
23,750 57
51,450 99
41,000 85
The resulting correlation coefficient is +.98 and the probability of insignificance is 3%.

Question 71

The goal of factor analysis is to identify as many factors as possible.

Question 72

Data mining does not draw upon statistics, artificial intelligence, database management, and computer science to identify patterns in market data sets.

Question 73

Multiple regression enables the researcher to show that two variables are causally related.

Question 74

Conjoint analysis is a standard procedure.

Question 75

The independent variables in multiple regression should not be correlated with each other.

Question 76

In factor analysis, naming factors is a somewhat subjective step, combining intuition and knowledge of the variables with an inspection of the variables that have high loadings on each factor.

Question 77

The purpose of factor analysis is data simplification.

Question 78

Collinearity is a situation in which independent variables are heavily correlated with each other.

Question 79

Cluster analysis is useful for clustering groups of questions together into factors.

Question 80

Regression analysis can prove causation.