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International Journal of Pure & Applied Bioscience (IJPAB)
Year : 2018, Volume : 6, Issue : 5
First page : (90) Last page : (96)
Article doi: : http://dx.doi.org/10.18782/2320-6924

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 ricecrop 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

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