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Copyright 2007 McGraw-Hill Pty LtdPPTs t/a Marketing Research 2e by Lukas, Hair, Bush and OrtinauSlides prepared by Judy Rex
16-1
Chapter SixteenData Analysis: Testing for Interdependence
Copyright 2007 McGraw-Hill Pty LtdPPTs t/a Marketing Research 2e by Lukas, Hair, Bush and OrtinauSlides prepared by Judy Rex
16-2
Learning Objectives
Describe interdependence techniques.
Define and understand factor analysis and cluster analysis.
Copyright 2007 McGraw-Hill Pty LtdPPTs t/a Marketing Research 2e by Lukas, Hair, Bush and OrtinauSlides prepared by Judy Rex
16-3
Introduction Assessing interdependence between
variables allows the researcher to summarise and understand a large number of independent variables.
Techniques for grouping X variables include: Factor analysis, to reduce and summarise
data. Cluster analysis, to classify objects.
Copyright 2007 McGraw-Hill Pty LtdPPTs t/a Marketing Research 2e by Lukas, Hair, Bush and OrtinauSlides prepared by Judy Rex
16-4
Interdependence TechniquesInterdependence exists when no
single variable or group of variables among those under consideration can be defined as being dependent or independent.
No one variable can be predicted or explained by the others.
Need to analyse all the variables in the data set simultaneously.
Copyright 2007 McGraw-Hill Pty LtdPPTs t/a Marketing Research 2e by Lukas, Hair, Bush and OrtinauSlides prepared by Judy Rex
16-5
Summary of Selected Interdependence Methods – Factor analysisFactor analysis is used to
summarise the information contained in a large number of variables into a smaller number of subsets called factors.
Copyright 2007 McGraw-Hill Pty LtdPPTs t/a Marketing Research 2e by Lukas, Hair, Bush and OrtinauSlides prepared by Judy Rex
16-6
Summary of Selected Interdependence Methods – Cluster AnalysisCluster analysis is used to
classify respondents or objects (e.g. products, stores) into groups that are homogeneous, or similar within the groups but different between groups.
Copyright 2007 McGraw-Hill Pty LtdPPTs t/a Marketing Research 2e by Lukas, Hair, Bush and OrtinauSlides prepared by Judy Rex
16-7
Classification of Multivariate Methods
Nominal
• Discriminant Analysis• Conjoint
Dependent VariableLevel of Measurement
Ordinal
• Spearman’s Rank Correlation
DependenceMethods
Number of Dependent Variables
Intervalor Ratio
• Multiple Regression• ANOVA• MANOVA• Conjoint
InterdependenceMethods
• Factor Analysis• Cluster Analysis• Perceptual Mapping
One None
(Metric)(Non-metric)
Copyright 2007 McGraw-Hill Pty LtdPPTs t/a Marketing Research 2e by Lukas, Hair, Bush and OrtinauSlides prepared by Judy Rex
16-8
Factor AnalysisA technique to summarise
information contained in a large number of variables into a smaller number of subsets or factors. To simplify the data. No distinction between X and Y
(dependent and independent variables), they are analysed together.
Copyright 2007 McGraw-Hill Pty LtdPPTs t/a Marketing Research 2e by Lukas, Hair, Bush and OrtinauSlides prepared by Judy Rex
16-9
Factor Analysis – Ratings of 6 characteristics of a fast food restaurant by 5 consumers.
Copyright 2007 McGraw-Hill Pty LtdPPTs t/a Marketing Research 2e by Lukas, Hair, Bush and OrtinauSlides prepared by Judy Rex
16-10
Factor Analysis - Factor Loadings
The correlation between each factor score and each of the original variables.
Each factor loading is a measure of the importance of the variable in measuring the factor.
From –1 to +1 A ‘high loading’ or correlation means
that the variable helps define the factor.
Copyright 2007 McGraw-Hill Pty LtdPPTs t/a Marketing Research 2e by Lukas, Hair, Bush and OrtinauSlides prepared by Judy Rex
16-11
Factor Analysis
Naming Factors Combine intuition and knowledge of
the variables with an inspection of the variables that have high loadings on each factor.
Copyright 2007 McGraw-Hill Pty LtdPPTs t/a Marketing Research 2e by Lukas, Hair, Bush and OrtinauSlides prepared by Judy Rex
16-12
Factor Analysis – Ratings of 6 characteristics of a fast food restaurant by 5 consumers.Example of a factor analysis application to a fast-food restaurant
Copyright 2007 McGraw-Hill Pty LtdPPTs t/a Marketing Research 2e by Lukas, Hair, Bush and OrtinauSlides prepared by Judy Rex
16-13
Question…Based on exhibit 16.1, which
variables comprise the service quality factor?
Based on exhibit 16.1, which variables comprise the food quality factor?
Copyright 2007 McGraw-Hill Pty LtdPPTs t/a Marketing Research 2e by Lukas, Hair, Bush and OrtinauSlides prepared by Judy Rex
16-14
Factor AnalysisHow many factors?
Look at the percentage of variation.
Factor Scores Produce composite variables when
applied to a number of variables. A factor is a weighted summary
score of a set of related variables.
Copyright 2007 McGraw-Hill Pty LtdPPTs t/a Marketing Research 2e by Lukas, Hair, Bush and OrtinauSlides prepared by Judy Rex
16-15
Factor AnalysisHow many factors to retain?
A complex process.How much does each factor
contribute to the understanding of the data?
Copyright 2007 McGraw-Hill Pty LtdPPTs t/a Marketing Research 2e by Lukas, Hair, Bush and OrtinauSlides prepared by Judy Rex
16-16
Factor Loading Example
Percentage variation in original date explained by each factor
Copyright 2007 McGraw-Hill Pty LtdPPTs t/a Marketing Research 2e by Lukas, Hair, Bush and OrtinauSlides prepared by Judy Rex
16-17
Applications of Factor Analysis in Marketing Research
Communication and promotionPricingProductDistribution
Copyright 2007 McGraw-Hill Pty LtdPPTs t/a Marketing Research 2e by Lukas, Hair, Bush and OrtinauSlides prepared by Judy Rex
16-18
Factor Analysis and Multiple Regression
Sometimes combining the results of Factor Analysis and Multiple regression can be helpful.
Copyright 2007 McGraw-Hill Pty LtdPPTs t/a Marketing Research 2e by Lukas, Hair, Bush and OrtinauSlides prepared by Judy Rex
16-19
Cluster AnalysisMarketing researchers draw upon
cluster analysis to classify objects or respondents into groups that have something in common.
Cluster analysis pinpoints what is homogeneous/similar within groups but heterogeneous/different between them.
Copyright 2007 McGraw-Hill Pty LtdPPTs t/a Marketing Research 2e by Lukas, Hair, Bush and OrtinauSlides prepared by Judy Rex
16-20
Cluster AnalysisAn Interdependence method—
why?Groups objects within each
group that are similar on a variety of measures.
Be aware of applications.
Copyright 2007 McGraw-Hill Pty LtdPPTs t/a Marketing Research 2e by Lukas, Hair, Bush and OrtinauSlides prepared by Judy Rex
16-21
Fast Food ExampleA fast food restaurant wants to
open an eat-in restaurant in a new area.
Collect data on demographics, lifestyles and expenditures on eating out.
Four potential clusters or segments.
Copyright 2007 McGraw-Hill Pty LtdPPTs t/a Marketing Research 2e by Lukas, Hair, Bush and OrtinauSlides prepared by Judy Rex
16-22
Cluster Analysis - Fast Food Example
Cluster analysis based on two characteristics
Copyright 2007 McGraw-Hill Pty LtdPPTs t/a Marketing Research 2e by Lukas, Hair, Bush and OrtinauSlides prepared by Judy Rex
16-23
Applications of Cluster Analysis in Marketing ResearchNew product researchTest marketingBuyer behaviourMarket segmentation
Copyright 2007 McGraw-Hill Pty LtdPPTs t/a Marketing Research 2e by Lukas, Hair, Bush and OrtinauSlides prepared by Judy Rex
16-24
Cluster Analysis and Discriminant Analysis
Sometimes combining the results of cluster analysis and discriminant analysis can be helpful.