FACTOR ANALYSIS

Factor analysis is a method of data reduction. There are many different methods that can be used to conduct a factor analysis along with a number of rotation techniques. Factor analysis is a technique that requires a large sample size. Factor analysis is based on the correlation matrix of the variables involved, and correlations usually need a large sample size before they stabilize (Professor James Sidanius).

Many statistical methods are used to study the relation between independent and dependent variables. Factor analysis is different; it is used to study the patterns of relationship among many dependent variables, with the goal of discovering something about the nature of the independent variables that affect them, even though those independent variables were not measured directly. Thus answers obtained by factor analysis are necessarily more hypothetical and tentative than is true when independent variables are observed directly. The inferred independent variables are called

*factors*(Professor Richard B. Darlington)Factor analysis find huge application in variety of fields including Psychology where it is most often associated with intelligence research. However, it also has been used to find factors in a broad range of domains such as personality, attitudes, beliefs, etc

Factor Analysis is also employed in the field of economics where it aims to see whether productivity, profits and workforce can be reduced down to an underlying dimension of company growth.

In the field of Marketing, Factor Analysis is employed as an interdependence technique. The complete set of interdependent relationships is examined. There is no specification of dependent variables, independent variables, or causality. Factor analysis assumes that all the rating data on different attributes can be reduced down to a few important dimensions. This reduction is possible because the attributes are related. The rating given to any one attribute is partially the result of the influence of other attributes. The statistical algorithm deconstructs the rating (called a raw score) into its various components, and reconstructs the partial scores into underlying factor scores. Thus Factor Analysis eventually is an important tool to construct perceptual maps and other product positioning devices. .

Nikhil Kumar

Marketing 2 Group

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