Factor Analysis is a data reduction technique that is used to reduce a data-set with large number of variables into fewer number of factors. In factor analysis technique the common variance from all the variables is extracted and it is represented as a common factor score. This score is a reduced representation (dimensional) of all the variables and can be used for any further analysis. As a part of the family of general linear model (GLM) this method has some assumptions that are required to be considered: linear relationship, no multi-collinearity, relevant variables, and correlation between variables and factors. There are many statistical methods available to perform factor analysis, such as principle component analysis, principle axis factoring etc.