Factor and Cluster Analysis
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Transcript of Factor and Cluster Analysis
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Factor Analysis and Cluster Analysis
Submitted by :
Akshay Patidar
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Factor Analysis
Factor analysis allows us to look at groups of
variables that tend to be correlated to each other
and identify underlying dimensions that explainthese correlations.
William D. Neal, Senior partner, SDRconsultancy
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Factor analysis is also called as exploratory factor
analysis (EFA) This technique has numerous
implications in marketing research as:
Can be used in market segmentation for ex: buyingnew car.
Can be employed to determine brand attributes thatinfluence customer choice for ex: toothpaste
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The main goal of factor analysis is datareduction. A typical use of factor analysis is insurvey research, where a researcher wishes torepresent a number of questions with a smallernumber of factors
Two questions in factor analysis: How many factors are there and what they represent
(interpretation)
Two technical aids: Eigen values Percentage of variance accounted for
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More on terminology
Factor loading: interpreted as the correlation betweenthe variable and the factor
Communality: the proportion of variability for a given
variable that is explained by the factor
Extraction: the process by which the factors aredetermined from a large set of variables
The sample size should be about 10 to 15 times of thenumber of variables.
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Theoretical basis
In factor analysis each variable is expressed
as a linear combination of underlying factors. If
the variables are standardized, the variables of
factor model may be represented as :
V1=L1*F1+E1
V2=L2*F1+E2
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Number of factors:
Eigen values are often used to determine how many
factors to take
Take as many factors there are having Eigen values>1
Eigen value represents the amount of standardized variance
in the variable accounted for by a factor
The sum of Eigen values is the percentage of variance
accounted for
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Conducting Factor
Analysis
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Criticisms of Factor Analysis
Labels of factors can be arbitrary or lack scientific basis
Garbage in, garbage out
really a criticism of input variables
Too many steps that could affect results Too complicated
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Cluster analysis
Cluster analysis helps in identifying groups or
segments that are more like each other than they are
like members of other groups or segments.
It examines the interdependent relationships
between the whole set of variables rather than
making distinction between dependent and
independent variables as in factor analysis.
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Conducting cluster analysis
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Source and references
Marketing research- Naresh k. Malhotra
Research methodology- C.R.Kothari
Marketing research- C.N.Sontakki
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Thank You and Keep smiling
