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Indian Journal of Pure & Applied Biosciences (IJPAB)
Year : 2018 , Volume 6, Issue 5
Page No. : 90-96
Article doi: : http://dx.doi.org/10.18782/2320-7051.6924
Prediction of Rice Production in Madhya Pradesh through a Multiple Regression Approach
Kuldeep Rajpoot1*, Abhishek Singh2 and Thanu Ram Jaiswal3
1,2Department of Farm Engineering, BHU, Varanasi, (U.P.), India
3Department of Mathematics & Statistics, JNKVV, Jabalpur-482004, (M.P.) India
*Corresponding Author E-mail: kuldeep2rajpoot@gmail.com
Received: 25.08.2018 | Revised: 21.09.2018 | Accepted: 28.09.2018
ABSTRACT
During the last few decades, the statisticians, economists and other scientists have given due consideration to see the performance of the production of rice crop based on area under cultivation, cost of labour, cost of seed, cost of fertilizer etc. In the present study the multiple regression model has been fitted using least square principle. The test for normality of errors, homogeneity of error variances and independence of serial correlation of error terms (no autocorrelation) in the model have been investigated.
Key words: Multiple regression, Autocorrelation, Durbin-Watson‘d’ statistic, Partial regression coefficients, Response and predictor variable, Rank correlation, J-B Test.
Full Text : PDF; Journal doi : http://dx.doi.org/10.18782/2320-7051.6924
Cite this article:
Rajpoot, K., Singh, A., and Jaiswal, T. R., Prediction of Rice Production in Madhya Pradesh through a Multiple Regression Approach, Int. J. Pure App. Biosci. 6(5): 90-96 (2018). doi: http://dx.doi.org/10.18782/2320-7051.6924
