Download Chapter 16

Survey
yes no Was this document useful for you?
   Thank you for your participation!

* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project

Document related concepts
no text concepts found
Transcript
Chapter Sixteen
Data Analysis:
Testing for Interdependence
Copyright  2007 McGraw-Hill Pty Ltd
PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau
Slides prepared by Judy Rex
16-1
Learning Objectives
 Describe interdependence
techniques.
 Define and understand factor
analysis and cluster analysis.
Copyright  2007 McGraw-Hill Pty Ltd
PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau
Slides prepared by Judy Rex
16-2
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 Ltd
PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau
Slides prepared by Judy Rex
16-3
Interdependence Techniques
Interdependence 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 Ltd
PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau
Slides prepared by Judy Rex
16-4
Summary of Selected
Interdependence Methods –
Factor analysis
 Factor 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 Ltd
PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau
Slides prepared by Judy Rex
16-5
Summary of Selected
Interdependence Methods –
Cluster Analysis
Cluster 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 Ltd
PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau
Slides prepared by Judy Rex
16-6
Classification of Multivariate
Methods
Dependence
Methods
(Non-metric)
Nominal
One
Number of
Dependent Variables
None
Interdependence
Methods
(Metric)
Dependent Variable
Level of Measurement
Interval
or Ratio
• Factor Analysis
• Cluster Analysis
• Perceptual Mapping
Ordinal
• Discriminant
Analysis
• Conjoint
• Spearman’s Rank
Correlation
• Multiple Regression
• ANOVA
• MANOVA
• Conjoint
Copyright  2007 McGraw-Hill Pty Ltd
PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau
Slides prepared by Judy Rex
16-7
Factor Analysis
 A 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 Ltd
PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau
Slides prepared by Judy Rex
16-8
Factor Analysis –
Ratings of 6 characteristics of a fast food
restaurant by 5 consumers.
Copyright  2007 McGraw-Hill Pty Ltd
PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau
Slides prepared by Judy Rex
16-9
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 Ltd
PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau
Slides prepared by Judy Rex
16-10
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 Ltd
PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau
Slides prepared by Judy Rex
16-11
Factor Analysis –
Ratings of 6 characteristics of a fast
food restaurant by 5 consumers.
Example of a factor analysis application to a fastfood restaurant
Copyright  2007 McGraw-Hill Pty Ltd
PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau
Slides prepared by Judy Rex
16-12
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 Ltd
PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau
Slides prepared by Judy Rex
16-13
Factor Analysis
 How 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 Ltd
PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau
Slides prepared by Judy Rex
16-14
Factor Analysis
How many factors to retain?
 A complex process.
 How much does each factor
contribute to the understanding
of the data?
Copyright  2007 McGraw-Hill Pty Ltd
PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau
Slides prepared by Judy Rex
16-15
Factor Loading Example
Percentage variation in original date
explained by each factor
Copyright  2007 McGraw-Hill Pty Ltd
PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau
Slides prepared by Judy Rex
16-16
Applications of Factor Analysis
in Marketing Research
Communication and promotion
Pricing
Product
Distribution
Copyright  2007 McGraw-Hill Pty Ltd
PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau
Slides prepared by Judy Rex
16-17
Factor Analysis and Multiple
Regression
Sometimes combining the results
of Factor Analysis and Multiple
regression can be helpful.
Copyright  2007 McGraw-Hill Pty Ltd
PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau
Slides prepared by Judy Rex
16-18
Cluster Analysis
 Marketing 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 Ltd
PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau
Slides prepared by Judy Rex
16-19
Cluster Analysis
 An 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 Ltd
PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau
Slides prepared by Judy Rex
16-20
Fast Food Example
A 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 Ltd
PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau
Slides prepared by Judy Rex
16-21
Cluster Analysis - Fast Food
Example
Cluster analysis based on two characteristics
Copyright  2007 McGraw-Hill Pty Ltd
PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau
Slides prepared by Judy Rex
16-22
Applications of Cluster Analysis
in Marketing Research
New product research
Test marketing
Buyer behaviour
Market segmentation
Copyright  2007 McGraw-Hill Pty Ltd
PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau
Slides prepared by Judy Rex
16-23
Cluster Analysis and
Discriminant Analysis
Sometimes combining the results
of cluster analysis and discriminant
analysis can be helpful.
Copyright  2007 McGraw-Hill Pty Ltd
PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau
Slides prepared by Judy Rex
16-24