The main purpose of factor analysis is to determine whether or not the correlations between a set of obwerved cariables can be explained in terms of a samll number of factors or latent variables. In exploratory ractor analysis(EFA), the main objective is to decide how many factors are needed to account adequately for the data. In the other hand, in confirmatory factor analysis (CFA), the researcher formulates a hypothesis that specifies the factors depending upon the measures variables. Then factor analysis is sued to test this hypothesis. The factor analysis model postulates that the observed variables are linear functions of the factor and a measurement error term. The equaions for the factor analysis model in matrix form can be written as folles: It we estimated the parameters in a factor analysis mode, we have to consider the model identificaion first. When swe have p observed variables, there are p(p+1)/2 known elements in the covariance matrix of x. is the number of free paramenters in necessary but not sufficient condition for identificaions is the following fule.