WHAT IS FACTOR ANALYSIS?
Factor analysis is a procedure aimed at finding out the underlying structure or dimension of a set of data. For example, you are interested in measuring personality and develop a test consisting of 20 items which you believe will establish whether a person is an extrovert or an introvert (see diagram below).
PERSONALITY TEST
20 Items or Questions
Extrovert
Introvert
EXAMPLE:
To determine if the 20 item personality measures the two dimensions hypothesised i.e. extrovert & introvert; factor analysis is used. Remember, factor analyis a procedure and there several statistical methods that can used to perform factor analysis to detect the underlying structure or dimension of a set of data. What factor analysis does is to summarise or reduce data by identifying the underlying dimension. Refering to the example above, you will have much smaller number of items than the original variable. From the original 20 items or variables, you could end up with two dimensions or factors or variables, i.e. introvert and extrovert.
FACTOR ANALYSIS IS AN 'INTERDEPENDENCE' TEACHNIQUE
Factor analysis is an 'interpendence technique' while MANOVA or Multiple Regression are called 'dependence techniques'.
  • Dependence techniques are those statistical procedures which requires you to identify variables as 'independent variables' and 'dependent variables' such as you would do when using MANOVA or Multiple Regression. 
  • Interdepence techniques are those statistical procedures in which ALL VARIABLES are considered simultaneously and each is related to each other. Underlying these interrelated items or variables are a "latent set of factors" or dimensions that are themselves made up of all other variables. In other words, there is no division of independent or dependent variables.

Underlying FACTORS or DIMENSIONS

Factor Analysis  (pg. 1)
a) What is factor analysis?
b) Why is factor analysis called an interdependence
   technique?
At the end of this topic you should be able to:
  • explain what is Factor Analysis
  • justify when to use Factor Analysis
  • determine the assumptions for using Factor Analysis
  • apply different types of statistical techniques used in Factor Analysis
  • interpret SPSS outputs from using Factor Analysis

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