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Marketing Research Applied Insight 6th Edition Daniel Nunan, David F. Burks, Naresh K. Malhotra - Solutions
1 Analyse the data in Table 25.1 using the following hierarchical methods:a Single linkage (nearest neighbour).b Complete linkage (furthest neighbour).c Method of centroid.
15 How is cluster analysis used to group variables?
14 Describe some procedures available for assessing the quality of clustering solutions.
13 What are some of the additional variables used for profiling the clusters?
12 What role may qualitative methods play in the interpretation of clusters?
11 What is involved in the interpretation of clusters?
10 What guidelines are available for deciding the number of clusters?
6 Present a classification of clustering procedures.
3 What are some of the uses of cluster analysis in marketing?
2 What is a ‘cluster’?
6 appreciate how software is used to carry out factor analysis.
5 discuss the applications of non-hierarchical clustering and clustering of variables;
4 describe the purpose and methods for evaluating the quality of clustering results and assessing reliability and validity;
3 explain the procedure for conducting cluster analysis, including formulating the problem, selecting a distance measure, selecting a clustering procedure, deciding on the number of clusters, interpreting clusters and profiling clusters;
2 discuss the statistics associated with cluster analysis;
1 describe the basic concept and scope of cluster analysis and its importance in marketing research;
5 In a small group, identify the uses of factor analysis in each of the following major decision areas in marketing:a Market segmentation b Product decisions c Promotions decisions d Pricing decisions e Distribution decisions f Service delivery decisions
4 You are a marketing research analyst for a manufacturer of fashion clothing targeted at teenage boys. You have been asked to develop a set of 10 statements for measuring psychographic characteristics and lifestyles that you feel would relate to their fashion personas. The participants would be
3 Analyse the Benetton data (taken from Exercise 4, Chapter 20). Consider only the following variables: awareness, attitude, preference, intention and loyalty towards Benetton.a Analyse these data using principal components analysis, using the varimax rotation procedure.b Interpret the factors
2 In a study of the relationship between household behaviour and shopping behaviour, data on the following lifestyle statements were obtained on a seven-point scale (1 = disagree, 7 = agree):V1 I would rather spend a quiet evening at home than go out to a party.V2 I always check prices, even on
1 Complete the following portion of an output from principal components analysis:Variable Communality Factor Eigenvalue % of variance V1 1.0 1 3.25 V2 1.0 2 1.78 V3 1.0 3 1.23 V4 1.0 4 0.78 V5 1.0 5 0.35 V6 1.0 6 0.30 V7 1.0 7 0.19 V8 1.0 8 0.12 a Draw a scree plot based on these data.b How many
15 How is the fit of the factor analysis model examined?
14 What are surrogate variables? How are they determined?
13 When is it useful to calculate factor scores?
12 What guidelines are available for interpreting the factors?
11 Why is it useful to rotate the factors? Which is the most common method of rotation?
10 What is a scree plot? For what purpose is it used?
5 What is meant by the term ‘communality of a variable’?
3 Describe the factor analysis model.
2 What are the major uses of factor analysis?
6 appreciate how software is used in factor analysis.
5 describe the procedure for determining the fit of a factor analysis model using the observed and the reproduced correlations;
4 explain the selection of surrogate variables and their application, with emphasis on their use in subsequent analysis;
3 understand the distinction between principal component factor analysis and common factor analysis methods;
2 discuss the procedure for conducting factor analysis, including problem formulation, construction of the correlation matrix, selection of an appropriate method, determination of the number of factors, rotation and interpretation of factors;
1 describe the concept of factor analysis and explain how it is different from analysis of variance, multiple regression and discriminant analysis;
4 In a small group, discuss the following issue: ‘Is it meaningful to determine the relative importance of predictors in discriminating between the groups?Why or why not?’
3 Analyse the Benetton data (taken from Exercise 4, Chapter 20). Do the three usage groups differ in terms of awareness, attitude, preference, intention and loyalty towards Benetton when these variables are considered simultaneously?
2 Given the following information, calculate the discriminant score for each participant. The value of the constant is 2.04.
1 In investigating the differences between heavy, light or non-users of frozen foods, it was found that the two largest standardised discriminant function coefficients were 0.97 for convenience orientation and 0.61 for income. Is it correct to conclude that convenience orientation is more important
15 How does the stepwise discriminant procedure differ from the direct method?
14 When the groups are of equal size, how is the accuracy of chance classification determined?
13 Describe a common procedure for determining the validity of discriminant analysis.
12 How is the statistical significance of discriminant analysis determined?
11 Explain the concept of structure correlations.
10 What is a classification matrix?
9 Explain what is meant by an eigenvalue.
8 Define discriminant scores.
7 What is Wilks’ l? For what purpose is it used?
1 What are the objectives of discriminant analysis?
6 understand the use of software to support discriminant and logit analysis.
5 describe the binary logit model and its advantages over discriminant and regression analysis;
4 explain stepwise discriminant analysis and describe the Mahalanobis procedure;
3 discuss multiple discriminant analysis and the distinction between two-group and multiple discriminant analysis;
2 outline the procedures for conducting discriminant analysis, including the formulation of the problem, estimation of the discriminant function coefficients, determination of significance, interpretation and validation;
1 describe the concept of discriminant analysis, its objectives and its applications in marketing research;
5 In a small group, discuss the following issues: ‘Regression is such a basic technique that it should always be used in analysing data’ and ‘What is the relationship between bivariate correlation, bivariate regression, multiple regression and analysis of variance?
4 In a survey pre-test, data were obtained from 20 participants on preference for boots 1V12 on a seven-point scale (1 = not preferred, 7 = greatly preferred). The participants also provided their evaluations of the boots on comfort 1V22, style 1V32 and durability 1V42, also on seven-point scales(1
2 To understand the role of quality and price in influencing the patronage of shoe shops, 14 major shoe shops in a large city were rated in terms of preference to shop, quality of shoes sold and price fairness. All the ratings were obtained on an 11-point scale, with higher numbers indicating more
1 A supermarket chain wants to determine the effect of promotion on relative competitiveness. Data were obtained from 15 cities on the promotional expenses relative to a major competitor (competitor expenses = 100) and on sales relative to this competitor (competitor sales = 100).
15 Demonstrate the equivalence of regression with dummy variables to one-way ANOVA.+
14 What are some of the measures used to assess the relative importance of predictors in multiple regression?
13 Describe the cross-validation procedure. Describe double cross-validation.
12 What is multicollinearity? What problems can arise because of multicollinearity?
11 Explain the stepwise regression approach. What is its purpose?
10 What is gained by an examination of residuals?
3 What is the least squares procedure?
2 What are the main uses of regression analysis?
6 understand the use of software in analyses of correlation and regression.
5 discuss non-metric correlation and measures such as Spearman’s rho and Kendall’s tau;
4 describe specialised techniques used in multiple regression analysis, particularly stepwise regression, regression with dummy variables and analysis of variance and covariance with regression;
3 explain the nature and methods of multiple regression analysis and the meaning of partial regression coefficients;
2 explain the nature and methods of bivariate regression analysis and describe the general model, estimation of parameters, standardised regression coefficient, significance testing, prediction accuracy, residual analysis and model cross-validation;
1 discuss the concepts of product moment correlation, partial correlation and part correlation, and show how they provide a foundation for regression analysis;
5 In a small group discuss the following issues: ‘Which procedure is more useful in marketing research – analysis of variance or analysis of covariance?’and ‘There are few marketing research applications where t tests are used;the complexity of marketing phenomena means that analysis of
4 In an experiment designed to measure the effect of gender and frequency of travel on preference for long-haul holidays, a 2 (gender) * 3 (frequency of travel) between-subjects design was adopted. Five participants were assigned to each cell for a total sample size of 30. Preference for long-haul
3 An experiment tested the effects of package design and shelf display on the likelihood of buying a breakfast cereal. Package design and shelf display were varied at two levels each, resulting in a 2 * 2 design. Purchase likelihood was measured on a seven-point scale. The results are partially
2 In a pilot study examining the effectiveness of three advertisements (A, B and C), 10 consumers were assigned to view each advertisement and rate it on a nine-point Likert scale. The data obtained from the 30 participants are shown in the following table:
1 A researcher wants to test the hypothesis that there is no difference in the importance attached to shopping by consumers living in Belgium, France, Germany and the Netherlands. A study is conducted and analysis of variance is used to analyse the data. The results obtained are presented in the
15 What is multivariate analysis of variance? When is it appropriate?
14 Describe two tests used for examining differences in central tendencies in non-metric ANOVA.
13 What are the differences between metric and non-metric analyses of variance?
12 What is meant by repeated measures ANOVA? Describe the decomposition of variation in repeated measures ANOVA.
11 What is the most powerful test for making a posteriori contrasts? Which test is the most conservative?
10 What is an a priori contrast?
7 What is the most common use of the covariate in ANCOVA?
2 What is the relationship between analysis of variance and the t test?
How do consumers’ intentions to buy the brand vary with different price levels?
Do retailers, wholesalers and agents differ in their attitudes towards the firm’s distribution policies?
Do brand evaluations of groups exposed to different advertisements vary?
Do various market segments differ in terms of their volume of product consumption?
4 In a survey pre-test, data were obtained from 45 participants on Benetton clothes. These data are given in the table overleaf, which gives the usage, gender, awareness, attitude, preference, intention and loyalty towards Benetton of a sample of Benetton users. Usage was coded as 1, 2 or 3,
3 An electrical goods chain is having a New Year sale of refrigerators. The number of refrigerators sold during this sale at a sample of 10 stores was 80 110 0 40 70 80 100 50 80 30 a Is there evidence that an average of more than 50 refrigerators per store was sold during this sale? Use a = 0.05.b
1 In each of the following situations, indicate the statistical analysis you would conduct and the appropriate test or test statistic that should be used:a Consumer preferences for The Body Shop shampoo were obtained on an 11-point Likert scale. The same consumers were then shown a commercial about
15 Which non-parametric tests are the counterparts of the paired samples t test for parametric data?
14 Which non-parametric tests are the counterparts of the two-independentsamples t test for parametric data?
13 What is the major difference between parametric and non-parametric tests?
12 Describe the general procedure for conducting a t test.
10 Discuss the reasons for the frequent use of cross-tabulations. What are some of the limitations?
8 Define a spurious correlation.
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