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Chapter Fifteen
Data Analysis:
Testing for Interdependence
Copyright  2004 McGraw-Hill Pty Ltd
PPTs t/a Marketing Research by Lukas, Hair, Bush and Ortinau
Slides prepared by Tony Peloso
15-1
Learning Objectives
 Describe interdependence
techniques
 Define and understand factor
analysis and cluster analysis
Copyright  2004 McGraw-Hill Pty Ltd
PPTs t/a Marketing Research by Lukas, Hair, Bush and Ortinau
Slides prepared by Tony Peloso
15-2
Introduction
PHASE III:
Execute the research
Marketing Research
Analyse the data
Step 8:
 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  2004 McGraw-Hill Pty Ltd
PPTs t/a Marketing Research by Lukas, Hair, Bush and Ortinau
Slides prepared by Tony Peloso
15-3
Summary of Selected
Interdependence Methods
 Factor analysis is used to summarise
the information contained in a large
number of variables into a smaller
number of subsets called factors.
 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  2004 McGraw-Hill Pty Ltd
PPTs t/a Marketing Research by Lukas, Hair, Bush and Ortinau
Slides prepared by Tony Peloso
15-4
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  2004 McGraw-Hill Pty Ltd
PPTs t/a Marketing Research by Lukas, Hair, Bush and Ortinau
Slides prepared by Tony Peloso
15-5
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—
analysed together
Copyright  2004 McGraw-Hill Pty Ltd
PPTs t/a Marketing Research by Lukas, Hair, Bush and Ortinau
Slides prepared by Tony Peloso
15-6
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 factor loading or correlation between
each variable and the factor it is
associated with
 ‘High loading’—the variable helps define
the factor
Copyright  2004 McGraw-Hill Pty Ltd
PPTs t/a Marketing Research by Lukas, Hair, Bush and Ortinau
Slides prepared by Tony Peloso
15-7
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  2004 McGraw-Hill Pty Ltd
PPTs t/a Marketing Research by Lukas, Hair, Bush and Ortinau
Slides prepared by Tony Peloso
15-8
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  2004 McGraw-Hill Pty Ltd
PPTs t/a Marketing Research by Lukas, Hair, Bush and Ortinau
Slides prepared by Tony Peloso
15-9
Factor Analysis—An Example
to Consider
Copyright  2004 McGraw-Hill Pty Ltd
PPTs t/a Marketing Research by Lukas, Hair, Bush and Ortinau
Slides prepared by Tony Peloso
15-10
Factor Analysis—Example to
Consider
Copyright  2004 McGraw-Hill Pty Ltd
PPTs t/a Marketing Research by Lukas, Hair, Bush and Ortinau
Slides prepared by Tony Peloso
15-11
Factor Loading for Example
 Service quality—because all
variables load on some aspect of
the service experience
 Food quality—related to food
 Can be a subjective process
 How many factors to retain?
 Be aware of applications
Copyright  2004 McGraw-Hill Pty Ltd
PPTs t/a Marketing Research by Lukas, Hair, Bush and Ortinau
Slides prepared by Tony Peloso
15-12
Cluster Analysis
 Interdependence method—why?
 Groups objects within each
group that are similar on a variety
of measures
 Be aware of applications
Copyright  2004 McGraw-Hill Pty Ltd
PPTs t/a Marketing Research by Lukas, Hair, Bush and Ortinau
Slides prepared by Tony Peloso
15-13
Cluster Analysis
 Marketing researchers draw upon
the power of cluster analysis to
classify objects or respondents
into groups that have something
in common.
 Cluster analysis pinpoints what is
similar within groups but
different between them.
Copyright  2004 McGraw-Hill Pty Ltd
PPTs t/a Marketing Research by Lukas, Hair, Bush and Ortinau
Slides prepared by Tony Peloso
15-14
Cluster Analysis—An
Example to Consider
Copyright  2004 McGraw-Hill Pty Ltd
PPTs t/a Marketing Research by Lukas, Hair, Bush and Ortinau
Slides prepared by Tony Peloso
15-15