Multivariate Techniques Research Process

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  • 1.Define multivariate analysis.

    2.Understand how to use multivariate analysis in marketing research.

    3.Distinguish between dependence and interdependence methods.

    4.Define and understand factor analysis and cluster analysis.

    5.Define and use discriminant analysis.Learning Objectives

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  • Multivariate analysis--statistical techniques used when there are two or more measurements of each element and the variables are analyzed simultaneously. Multivariate techniques are concerned with the simultaneous relationships among two or more phenomena.

    Important in marketing research because most business problems are multidimensional

    Define multivariate analysisValue of Multivariate Techniques in Data Analysis

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  • Exhibit 17.1Define multivariate analysis

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  • Exhibit 17.2Define multivariate analysis

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  • Dependence Method multivariate technique appropriate when one or more of the variables can be identified as dependent variables and the remaining as independent variables

    Dependence techniquesmultiple regression analysis, discriminant analysis, and MANOVA

    Multiple discriminant analysisdependence technique which predicts customer usage based on several independent variablesAge, income, peer group, education, lifestyle.

    Dependence MethodClassification Multivariate Techniques

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  • Interdependence techniques multivariate statistical techniques in which a whole set of interdependent relationships is examinedNo single variable is defined as dependent or independent

    Multivariate procedureanalysis of all variables in the data set simultaneously

    Goal of this methodto group things togetherSimplify data

    No one variable is predicted or explained by the others

    Interdependence techniques factor analysis, cluster analysis, Perceptual Mapping and multidimensional scalingInterdependence techniquesClassification Multivariate Techniques

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  • Nature of the Measurement Scales

    Determine which multivariate technique is appropriate to analyze the data Dependence vs. Interdependence

    Dependent variable

    Measured nonmetrically(Nominal)Discriminant analysis, Conjoint

    Measured metrically (ratio or interval) multiple regression, ANOVA, and MANOVA

    First StepClassification Multivariate Techniques

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  • Independent variable

    Require metric independent variablemultiple regression and discriminant analysiscan use nonmetric dummy variables

    Nonmetric independent variablesANOVA and MANOVA

    Metrically measured variables and nonmetric adaptionsfactor analysis and cluster analysis

    Classification Multivariate Techniques

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  • Factor Analysisused to summarize information contained in a large number of variables into a smaller number of subsets or factors

    Purpose of Factor Analysisto simplify the data

    No distinction between dependent and independent variables

    all variables under investigation are analyzed togetherto identify underlying factors

    Factor Analysis Interdependence Techniques

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  • Factor Analysis Exhibit 17.3

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  • Factor Loadingsimple correlation between the variables

    Starting Pointinterpreting factor analysis is factor loadings

    Factor loadingmeasure of the importance of the variable in measuring each factor

    Like correlationsvary from +1.0 to 1.0

    Statistical analysis associated with factor analysisproduces factor loadings between each factor and each of the original variablesFactor Analysis Interdependence Techniques

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  • Factor Analysis Exhibit 17.4

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  • Next Step in Factor Analysisname the resulting factorsFactor 1 Service QualityFactor 2 Food Quality

    Final Aspect of Factor Analysisthe number of factors to retain

    Factor Analysis Interdependence Techniques

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  • Factor Analysis Exhibit 17.5

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  • Factor Analysis Applications in Marketing Research

    Advertisingto better understand media habits of various customers

    Pricingto identify the characteristics of price-sensitive and prestige-sensitive customers

    Productto identify brand attributes that influence consumer choice

    Distributionto better understand channel selection criteria among distribution channel members

    Define and understand factor analysis and cluster analysisInterdependence Techniques

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  • Define and understand factor analysis and cluster analysisExhibit 17.6

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  • Define and understand factor analysis and cluster analysisExhibit 17.7

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  • Define and understand factor analysis and cluster analysisExhibit 17.8

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  • Define and understand factor analysis and cluster analysisExhibit 17.9

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  • Define and understand factor analysis and cluster analysisExhibit 17.10

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  • Cluster analysismultivariate interdependence technique whose primary objective is to classify objects into relatively homogeneous groups based on the set of variables considered

    Basic Purpose

    To classify or segment objects into groups so that objects within each group are similar to one another on a variety of variables

    To classify segments or objects such that there will be as much similarity within segments and as much difference between segments as possible

    To identify natural groupings or segments among many variables, without designating any of the variables as a dependent variable

    Cluster analysisInterdependence Techniques

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  • Cluster analysisExhibit 17.11

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  • Statistical Procedures for Cluster Analysis

    Degree of similarity between objectsdetermined through a distance measure

    Distance between any pair of points is positively related to how similar the corresponding individuals are when the two variables are considered together

    Cluster analysisInterdependence Techniques

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  • Clustersdeveloped from scatter plots

    This is a very complex, trial and error process

    Requires the use of computer algorithmsCluster analysis Scatter PlotsInterdependence Techniques

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  • Applications in Marketing Research

    New product researchto examine product offerings relative to competition

    Test marketingto group test cities into homogeneous clusters for test marketing purposes

    Buyer behaviorto identify similar groups of buyers who have similar choice criteria

    Market segmentationto develop distinct market segments on the basis of geographic, demographic, psychographic, and behavioral variablesCluster analysisInterdependence Techniques

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  • Define and understand factor analysis and cluster analysisExhibit 17.12

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  • SPSS exercise Use the Santa Fe databaseFind different subgroups of customers with different levels of commitmentUse Variables 22, 23,24Anaylse-classify-hierarchical clusterSelect wards methodSave box select 2 This procedure takes time

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  • Define and understand factor analysis and cluster analysisExhibit 17.13

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  • Define and understand factor analysis and cluster analysisExhibit 17.14

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  • Define and understand factor analysis and cluster analysisExhibit 17.15

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  • End Here

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  • Discriminant Analysismultivariate procedure used for predicting group membership on the basis of two or more independent variables

    Purposeto classify objects or groups by a set of independent variables

    Dependent variablenonmetric or categorical

    Independent variablesmetric

    Define and use discriminant analysisAnalysis of Dependence

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  • Define and understand factor analysis and cluster analysisExhibit 17.17

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  • Purpose of discriminant analysisprediction of a categorical variable by studying the direction of group differences based on finding a linear combination of independent variables

    Discriminant functionlinear combination of independent variables developed by discriminant analysis which will best discriminate between the categories of the dependent variable

    Discriminate analysisstatistical tool for determining linear combinations of those independent variables and using this to predict group membership

    Define and use discriminant analysisAnalysis of Dependence

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  • Discriminant score (Z-score)basis for predicting to which group the particular individual belongs and is determined by a linear functionZi=b1X1i + b2X2i + bnXni

    Zi=ith individuals discriminant score

    bn=Discriminant coefficient for the nth variable

    Xni=Individuals value on the nth independent variable

    Discriminant scorethe score of each respondent on the discriminant function

    Define and use discriminant analysisAnalysis of Dependence

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  • Discriminant function coefficientsestimates of the discriminatory power of a particular independent variable

    multipliers of variables in the discriminant function when variables are in the original units of measurement

    Coefficientscomputed by means of the discriminant analysis software

    Define and use d

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