Prediction of gross cropped area in Madhya Pradesh through a multiple regression approach

Chetan Patel; KS Kushwaha

Prediction of gross cropped area in Madhya Pradesh through a multiple regression approach

Author(s):

Chetan Patel and KS Kushwaha

Abstract:

Indian agriculture is a land-based activity and as such water and land have been the basic elements of life support system and is an important resource for the economic life of a majority of people in the country. The pattern of land use is not uniform but it changes from place to place and time to time. The gross cropped area (Y), forest area (X₁), area not available for cultivation (X₂), area for other uncultivable land (X₃), and area of fallow land (X₄), are varying from year to year in Madhya Pradesh.

The multiple Regression model may describe the pattern and projection of total cropped area based on predictor variables (x₁, x₂, x₃, x₄). In order to get evidence about the applicability of multiple regression procedure, Jarqua-Bera (J.B.) test, histogram of residuals, normal probability plot to test normality of errors, spearman’s rank correlation test for homogeneity of errors and Durbin-Watson ‘d’ statistic to test the independence of autocorrelation in error terms have been applied on secondary data of variables (y, x₁, x₂, x₃, and x₄) in M.P. state for 31 years.

Pages: 82-88 | 1378 Views 230 Downloads

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Journal of Pharmacognosy and Phytochemistry

How to cite this article:

Chetan Patel and KS Kushwaha. Prediction of gross cropped area in Madhya Pradesh through a multiple regression approach. J Pharmacogn Phytochem 2019;8(1):82-88.

Pharmacognosy

Journal of Pharmacognosy and Phytochemistry

Vol. 8, Issue 1 (2019)

Prediction of gross cropped area in Madhya Pradesh through a multiple regression approach

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