Industrial Production data is the key to study the growth and development of a nation. The data needs to be disseminated before formulating any models for prediction. Factor Analysis a key tool in multivariate statistics and has been used to determine the latent factors that best explain the data. In addition Principal ComponentAnalysis framework has been used for analyzing the data with respect to the contribution of variability by each of the components. The multiplicative models has been examined for its initial strength of the relationship for the production data and validation of the same has been discussed. The data has been processed for the removal of outliers, if any.

Key words : Production Data, Principal Component Analysis, Communalities, Component Matrix, Rotated Component
Matrix and Outliers.