• S. Loidang Devi

This paper consists of two models. One is usual multiple linear regression model and the another is principal component regression model. Primary data is used for this analysis. Findings show that the models fit the data well. Diagnostic checks confirmed that data do not seem to contradict the general underlying assumptions about the models. The value of Multiple correlation found in the usual regression model suggest that out of the total variation, 92.4% of variation in the yield of paddy is explained by the independent variable under consideration whereas 88.1% of variation is explained by principal component under study as shown by the principal component regression model.

Statistical Model, Stratified two-stage sampling scheme, Primary data, Multicollinearity, etc.

"A STUDY ON CAPARISON OF SOME STATISTICAL MODELS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.4, Issue 12, page no.104-108, December-2017, Available :http://www.jetir.org/papers/JETIR1712195.pdf

"A STUDY ON CAPARISON OF SOME STATISTICAL MODELS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.4, Issue 12, page no. pp104-108, December-2017, Available at : http://www.jetir.org/papers/JETIR1712195.pdf