## Exam

# Chapter 24—Multivariate Statistical Analysis. All ANswers

Chapter 24—Multivariate Statistical Analysis TRUE/FALSE 1. Multivariate statistical analysis permit the researcher to consider the effects of three or more variables at the same time. T PTS: 1 DIF: Moderate REF: p. 583 OBJ: LO: 24-01 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Knowledge 2. The variate is a mathematical way in which a set of variables can be represented with one equation. T PTS: 1 DIF: Moderate REF: p. 583 OBJ: LO: 24-01 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Knowledge 3. The basic types of multivariate techniques are primary methods and secondary methods. F The two basic types of mulitvariate techniques are dependence methods and interdependence methods. PTS: 1 DIF: Moderate REF: p. 584 OBJ: LO: 24-01 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Knowledge 4. Cluster analysis is a type of interdependence method. T PTS: 1 DIF: Moderate REF: p. 584 OBJ: LO: 24-01 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Knowledge 5. The type of measurement scales used does not influence which multivariate statistical techniques are appropriate for the data. F The type of measurement scales used will determine which multivariate statistical techniques are appropriate for the data. PTS: 1 DIF: Moderate REF: p. 585 OBJ: LO: 24-01 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Knowledge 6. Nominal and ordinal scales are referred to as nonmetric scales. T PTS: 1 DIF: Moderate REF: p. 585 OBJ: LO: 24-01 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Knowledge 7. The general linear model is a way of explaining and predicting a dependent variable based on fluctuations (variation) from its mean, with the fluctuations due to changes in independent variables. T PTS: 1 DIF: Moderate REF: p. 586 OBJ: LO: 24-01 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Knowledge 8. Multiple regression analysis includes a single independent variable but several dependent variables. F Multiple regression analysis is an extension of simple regression analysis allowing a metric dependent variable to be predicted by multiple independent variables. PTS: 1 DIF: Moderate REF: p. 586 OBJ: LO: 24-01 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Comprehension 9. Mulitvariate dependence techniques are variants of the general linear model (GLM). T PTS: 1 DIF: Moderate REF: p. 587 OBJ: LO: 24-01 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Comprehension 10. In multiple regression, the dependent and independent variables must be metric measures. F Less-than interval (nonmetric) independent variables can be used in multiple regression, which can be done by implementing dummy variable coding. PTS: 1 DIF: Moderate REF: p. 587 OBJ: LO: 24-01 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Comprehension 11. In multiple regression, dummy variables are those that have no effect on the dependent variable. F A dummy variable uses 0 and 1 to code the different levels of a dichotomous variable. PTS: 1 DIF: Moderate REF: p. 585 OBJ: LO: 24-01 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Knowledge 12. Partial correlations measure the variance inflation among independent variables. F Partial correlation is the correlation between two variables after taking into account the fact that they are correlated with other variables too. PTS: 1 DIF: Moderate REF: p. 588 OBJ: LO: 24-02 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Knowledge 13. In multiple regression, the coefficient of multiple determination, or 2, indicates the percentage of the variation in Y that can be explained by all independent variables. F The coefficient of multiple determination is denoted as R2. PTS: 1 DIF: Hard REF: p. 588 OBJ: LO: 24-02 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Knowledge 14. Multicollinearity in regression analysis refers to how strongly interrelated the independent variables in a model are. T PTS: 1 DIF: Moderate REF: p. 590 OBJ: LO: 24-02 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Knowledge 15. MANOVA predicts multiple continuous dependent variables with multiple continuous independent variables. F The independent variables are categorical. PTS: 1 DIF: Moderate REF: p. 591 OBJ: LO: 24-03 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Knowledge 16. Discriminant analysis predicts a categorical dependent variable based on a linear combination of independent variables. T PTS: 1 DIF: Moderate REF: p. 592 OBJ: LO: 24-05 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Knowledge 17. To determine whether the discriminant analysis can be used as a good predictor, information provided in the factor profile is used. F To determine whether the discriminant analysis can be used as a good predictor, information provided in the “confusion matrix” is used. PTS: 1 DIF: Moderate REF: p. 594 OBJ: LO: 24-05 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Comprehension 18. The most common rule for extracting factors in factor analysis is to base the number of factors on the number of eigenvalues greater than 1.0 T PTS: 1 DIF: Moderate REF: p. 596 OBJ: LO: 24-04 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Knowledge 19. A factor loading indicates how strongly a measured variable is correlated with a factor. T PTS: 1 DIF: Easy REF: p. 596 OBJ: LO: 24-04 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Knowledge 20. Factor rotation is a mathematical way of simplifying factor results. T PTS: 1 DIF: Easy REF: p. 597 OBJ: LO: 24-04 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Knowledge 21. Factor analysis is considered a data reduction technique. T PTS: 1 DIF: Easy REF: p. 597 OBJ: LO: 24-04 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Comprehension 22. The rule of parsimony basically means “less is better.” T PTS: 1 DIF: Moderate REF: p. 597 OBJ: LO: 24-04 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Comprehension 23. In factor analysis, communality is a measure of the percentage of a variable's variation that can be explained by the factors. T PTS: 1 DIF: Moderate REF: p. 598 OBJ: LO: 24-04 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Comprehension 24. In cluster analysis, each cluster should have low internal homogeneity and high external heterogeneity. F The cluster should have high internal (within-cluster) homogeneity and external (between-cluster) heterogeneity. PTS: 1 DIF: Hard REF: p. 599 OBJ: LO: 24-06 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Comprehension 25. Multidimensional scaling provides a means for placing objects in multidimensional space on the basis of respondents’ judgments of the similarity of objects. T PTS: 1 DIF: Moderate REF: p. 601 OBJ: LO: 24-06 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Knowledge MULTIPLE CHOICE 1. Which type of analysis involves three or more variables? a. univariate statistical analysis b. bivariate statistical analysis c. multivariate statistical analysis d. all of these choices C PTS: 1 DIF: Moderate REF: p. 583 OBJ: LO: 24-01 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Knowledge 2. Which of the following is a mathematical way in which a set of variables can be represented with one equation? a. structuralism b. variate c. ANOVA d. synergy B PTS: 1 DIF: Moderate REF: p. 583 OBJ: LO: 24-01 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Knowledge 3. The two basic groups of multivariate techniques are _____. a. dependence methods and interdependence methods b. primary methods and secondary methods c. simple methods and complex methods d. partial methods and complete methods A PTS: 1 DIF: Moderate REF: p. 584 OBJ: LO: 24-01 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Knowledge 4. When a multivariate statistical technique is used to predict job satisfaction from several independent variables, such as age, salary, and number of years in that position, the researcher is studying _____. a. dependence b. independence c. interdependence d. segments A PTS: 1 DIF: Hard REF: p. 584 OBJ: LO: 24-01 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Application 5. Which of the following is a dependence method of analysis? a. structural equations modeling b. multiple regression analysis c. multiple discriminant analysis d. all of these choices D PTS: 1 DIF: Easy REF: p. 584 OBJ: LO: 24-01 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Knowledge 6. All of the following are examples of dependence methods of analysis EXCEPT _____. a. multiple regression analysis b. multiple discriminant analysis c. cluster analysis d. multivariate analysis of variance C PTS: 1 DIF: Hard REF: p. 584 OBJ: LO: 24-01 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Knowledge 7. Which of the following is an example of an interdependence analysis method? a. multidimensional scaling b. multiple regression analysis c. conjoint analysis d. all of these choices A PTS: 1 DIF: Moderate REF: p. 584 OBJ: LO: 24-01 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Knowledge 8. All of the following are examples of interdependence methods of analysis EXCEPT _____. a. factor analysis b. cluster analysis c. multidimensional scaling d. conjoint analysis D PTS: 1 DIF: Hard REF: p. 584 OBJ: LO: 24-01 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Knowledge 9. Nominal and ordinal scales are examples of ______ scales, while interval and ratio scales are examples of ______ scales. a. metric; co-metric b. nonmetric; metric c. nonmetric; advanced d. metric; continuous B PTS: 1 DIF: Moderate REF: p. 585 OBJ: LO: 24-01 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Knowledge 10. If the analysis contains only one dependent variable and that variable is metric, the appropriate statistical analysis is: a. multiple discriminant analysis b. conjoint analysis c. multivariate ANOVA d. multiple regression D PTS: 1 DIF: Hard REF: p. 585 OBJ: LO: 24-01 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Comprehension 11. Which of the following is an appropriate technique when the inputs are metric? a. cluster analysis b. metric multidimensional scaling c. factor analysis d. all of these choices D PTS: 1 DIF: Easy REF: p. 585 OBJ: LO: 24-01 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Knowledge 12. Mulitvariate dependence techniques are variants of the _____, which is a way of modeling some process based on how different variables cause fluctuations from the average dependent variable. a. ordinary linear model (OLM) b. weighted average model (WAM) c. general linear model (GLM) d. metric scaling model (MSM) C PTS: 1 DIF: Moderate REF: p. 586 OBJ: LO: 24-01 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Knowledge 13. When a researcher is attempting to predict sales volume by using building permits, amount of advertising, and the income levels of residents, the researcher is using _____. a. univariate analysis b. a chi-square analysis c. multiple regression analysis d. factor analysis C PTS: 1 DIF: Hard REF: p. 586 OBJ: LO: 24-01 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Application 14. In regression analysis, the symbol X is commonly used for the ______ variable, and the symbol Y is commonly used for the ______ variable. a. dependent; moderating b. independent; dependent c. dependent; independent d. independent; moderating B PTS: 1 DIF: Moderate REF: p. 587 OBJ: LO: 24-01 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Knowledge 15. Which analysis is portrayed by the equation: Y = b b1X1 b2X2 b3X3... bnXn? a. simple regression b. multiple regression c. chi-square d. factor analysis B PTS: 1 DIF: Moderate REF: p. 587 OBJ: LO: 24-01 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Comprehension 16. A variable that is coded as either zero or one and that has two distinct levels is called a(n) _____. a. regression variable b. dummy variable c. MANOVA variable d. ANOVA variable B PTS: 1 DIF: Moderate REF: p. 587 OBJ: LO: 24-01 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Knowledge 17. The correlation between two variables after taking into account the fact that they are correlated with other variables too is called _____. a. partial correlation b. standardized correlation c. raw correlation d. variant correlation A PTS: 1 DIF: Moderate REF: p. 586 OBJ: LO: 24-02 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Knowledge 18. If the regression equation is: Y = 98.3 .35X1 22.3X2, the predicted value for Y when X1 = 3 and X2 = 5 is _____. a. 118.45 b. 210.85 c. 67.23 d. 98.3 B PTS: 1 DIF: Hard REF: p. 588 OBJ: LO: 24-02 NAT: AACSB Analytic| CB&E Model Research| Blooms Application 19. A value of R2 = 0.40 means that _____ percent of the variance in the dependent variable is explained by the independent variables. a. 80 b. 60 c. 40 d. 16 C PTS: 1 DIF: Hard REF: p. 588 OBJ: LO: 24-02 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Comprehension 20. In the following formula, k stands for: a. the number of observations b. the degrees of freedom of the denominator c. the number of independent variables d. the sample size C PTS: 1 DIF: Hard REF: p. 590 OBJ: LO: 24-02 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Knowledge 21. In the formula for the F-test in multiple regression, n - k - 1 represents the ____. a. degrees of freedom of the numerator b. number of observations c. degrees of freedom of the denominator d. number of independent variables C PTS: 1 DIF: Hard REF: p. 590 OBJ: LO: 24-02 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Knowledge 22. _____ is the extent to which independent variables in a multiple regression analysis are correlated with each other. a. Convergence b. Variance c. Skedacity d. Multicollinearity D PTS: 1 DIF: Moderate REF: p. 590 OBJ: LO: 24-02 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Knowledge 23. A researcher is analyzing data and is concerned over how strongly interrelated the independent variables of attitude toward one’s employer and attitude toward one’s coworkers are in his model. The researcher is concerned about _____. a. multicollinearity b. MANOVA c. degrees of freedom d. convergence A PTS: 1 DIF: Hard REF: p. 590 OBJ: LO: 24-02 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Application 24. Which of the following is computed by most regression programs and provide an indication of how much multicollinearity exists among a set of independent variables? a. 2 b. c. collinear coefficient d. variance inflation factor (VIF) D PTS: 1 DIF: Moderate REF: p. 590 OBJ: LO: 24-02 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Knowledge 25. Which of the following suggests problems with multicollinearity? a. VIF > 5.0 b. < 3.0 c. Power > 0.8 d. > 0.8 A PTS: 1 DIF: Moderate REF: p. 590 OBJ: LO: 24-02 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Knowledge 26. If the analysis predicts several continuous dependent variables with several categorical independent variables, the appropriate statistical technique is _____. a. multiple regression b. multiple discriminant analysis c. conjoint analysis d. MANOVA D PTS: 1 DIF: Moderate REF: p. 591 OBJ: LO: 24-03 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Knowledge 27. Which type of analysis attempts to predict a categorical dependent variable? a. factor analysis b. discriminant analysis c. regression analysis d. linear analysis B PTS: 1 DIF: Moderate REF: p. 592 OBJ: LO: 24-05 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Knowledge 28. If a bank wants to differentiate between successful and unsuccessful credit risks for home mortgage loans, it should use _____. a. factor analysis b. multidimensional scaling c. MANOVA d. discriminant analysis D PTS: 1 DIF: Hard REF: p. 592 OBJ: LO: 24-05 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Application 29. In discriminant analysis, a linear combination of independent variables that explains group memberships is known as a(n) _____. a. regression equation b. discriminant function c. discriminant factor d. n-way ANOVA B PTS: 1 DIF: Moderate REF: p. 592 OBJ: LO: 24-05 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Knowledge 30. Which multivariate analysis statistically identifies a reduced number of factors from a larger number of measured variables? a. factor analysis b. regression c. discriminant analysis d. logit analysis A PTS: 1 DIF: Moderate REF: p. 595 OBJ: LO: 24-04 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Knowledge 31. A researcher has 57 variables in a large dataset and wishes to summarize the information from them into a reduced set of variables. Which multivariate technique should be used? a. factor analysis b. multidimensional scaling c. logit analysis d. regression analysis A PTS: 1 DIF: Hard REF: p. 595 OBJ: LO: 24-04 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Hard 32. If a researcher wants to know how strongly a measured variable is correlated with a factor, what should she look at? a. factor b. discriminator c. factor link d. factor loading D PTS: 1 DIF: Hard REF: p. 596 OBJ: LO: 24-04 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Application 33. A mathematical way of simplifying factor analysis results is _____. a. factor loading b. factor reduction c. factor rotation d. factor analysis C PTS: 1 DIF: Moderate REF: p. 597 OBJ: LO: 24-04 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Knowledge 34. Which of the following suggests that an explanation involving fewer components is better than one involving more? a. rule of twos b. rule of parsimony c. data reduction rule d. min-max rule B PTS: 1 DIF: Moderate REF: p. 597 OBJ: LO: 24-04 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Knowledge 35. How can a researcher create a composite scale with factor results? a. The researcher can select the items with high R2 values and average them to form a composite scale. b. The researcher can sum the variables with high loadings on a factor to create a summated scale. c. The researcher can sum the variables with high VIF values on a factor to create a summated scale. d. The research can sum the items with high commonality values on a factor to create a summated scale. B PTS: 1 DIF: Hard REF: p. 598 OBJ: LO: 24-04 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Comprehension 36. Which of the following is a measure of the percentage of a variable’s variance that is explained by the factors in factor analysis? a. R2 b. variance inflation factor c. partial correlation d. communality D PTS: 1 DIF: Hard REF: p. 598 OBJ: LO: 24-04 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Comprehension 37. Which mulitvariate technique groups observations based on similarity among measured variables? a. regression b. cluster analysis c. conjoint analysis d. MANOVA B PTS: 1 DIF: Moderate REF: p. 599 OBJ: LO: 24-06 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Knowledge 38. In cluster analysis, the researcher wants clusters to have high ______ within-clusters and high between-cluster ______. a. independence; dependence b. significance; insignificance c. heterogeneity; homogeneity d. homogeneity; heterogeneity D PTS: 1 DIF: Hard REF: p. 599 OBJ: LO: 24-06 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Comprehension 39. Which mulitvariate techniques measures objects in multidimensional space on the basis of respondents’ judgments of the similarity of objects? a. factor analysis b. multidimensional scaling c. structured dimensional modeling d. relative positioning B PTS: 1 DIF: Moderate REF: p. 601 OBJ: LO: 24-06 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Knowledge 40. General Mills would like to “see” a picture of how its brands are perceived by consumers compared to competitive brands. Which statistical technique can measure brands in multidimensional space on the basis of respondents’ judgements of the similarity of the brands? a. structural equations modeling b. factor analysis c. multidimensional scaling d. partial positioning C PTS: 1 DIF: Hard REF: p. 601 OBJ: LO: 24-06 NAT: AACSB Reflective Thinking| CB&E Model Research| Blooms Application COMPLETION 1. Statistical methods that permit the study of three or more variables at the same time are called ______ statistical analysis. 2. The two types of multivariate techniques are ______ methods and ______ methods. 3. Multivariate techniques that try to group things together are known as ______ methods. 4. Multivariate dependence techniques are variants of the _____. 5. When an analysis studies the effect of several independent variables on a single dependent variable that is interval-scaled, this is called ______ analysis. 6. A ______ variable has two distinct levels that are coded as 0 and 1. 7. The test used to test statistical significance by comparing variation explained by the regression equation to the residual error variation is the _____. 8. _____ in regression analysis refers to how strongly interrelated the independent variables in a model are. 9. ______ predicts several dependent variables by using several independent variables. 10. If the researcher wants to classify objects into two mutually exclusive categories, the researcher should use ______ analysis. 11. The purpose of ______ analysis is to summarize information in a large number of variables into a smaller number of factors. 12. An indication of how strongly a measured variable is correlated with a factor is given by the _____. 13. A mathematical way of simplifying factor results is _____. 14. A multivariate interdependence technique that classifies individuals or objects into a small number of mutually exclusive and exhaustive groups is _____. 15. A statistical technique that measures objects in multidimensional space on the basis of respondents’ judgments of the similarity of objects is _____. ESSAY 1. Compare and contrast dependence and interdependence techniques. List the statistical techniques for both. When hypotheses involve distinction between independent and dependent variables, dependence 2. List the steps in interpreting a multiple regression model. Multiple regression models can be interpreted using these steps: (1) Examine the model F-test for significance. 3. Explain how MANOVA models differ from ANOVA models. An ANOVA or MANOVA model represent a form of the general linear model (GLM). ANOVA can be extended beyond one-way ANOVA to predict a dependent variable with multiple categorical 4. Explain why and how a business researcher uses factor analysis. Factor analysis is a prototypical multivariate, interdependence technique. It is a technique of statistically identifying a reduced number of factors from a larger number of measured variables. 5. Explain how cluster analysis can identify market segments. Cluster analysis is a multivariate approach for identifying objects or individuals that are similar to one