International Journal of Statistics and Applied Mathematics
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International Journal of Statistics and Applied Mathematics

2022, Vol. 7, Issue 2, Part A

A statistical SWOT up on garbled agricultural disparity at grassroot levels: A statistical analysis at block levels of Sambalpur district


Author(s): Suru Munda, Dr. Rajendra Gartia, Dr. Digambara Chand, Pritipadma Sahu and Deepak Kumar Behera

Abstract: Agriculture is the strength of Indian economy which provides employment for approximately 65% ​​of the workforce across the country. Regional inequality due to the unequal level of agricultural developments remains a major problem in India and Odisha in particular. In the present study, an attempt has been made to study the regional inequality in agricultural development among the nine blocks of Sambalpur district. The study utilizes published data obtained from Statistical Abstract of different districts in Western Odisha and ‘District Outlines’ published annually by the Directorate of Economics and Statistics (DES), Government of Odisha, for the year 2015-2016. Using technique of Principal Component Analysis (PCA), Seven Principal component were extracted which were found to be normally distributed by Kolmogorov Smirnov test. The three Quartiles Q1, Q2 and Q3 of the Normal probability distributions are used to classify the nine blocks into four homogeneous groups namely Meteoric, Progressive, Mediocre and Laggard on the basis of their composite index scores. The analysis finds that three blocks namely Dhankauda, Jamankira and Jujumura have the highest level of agricultural developments and are the Meteoric while two blocks namely Bamra and Naktideul have the lowest level of development and can be categorised as Laggard blocks. Kuchinda and Maneswar blocks are relatively less developed than Dhankauda, Jamankira and Jujumura and can be categorised as Progressive blocks while Rengali and Rairakhol are relatively more developed than the Lagard blockes and less developed than the Progressive blocks in terms of agricultural developments and may be treated as Mediocre blocks.

DOI: 10.22271/maths.2022.v7.i2a.811

Pages: 68-75 | Views: 142 | Downloads: 33

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How to cite this article:
Suru Munda, Dr. Rajendra Gartia, Dr. Digambara Chand, Pritipadma Sahu, Deepak Kumar Behera. A statistical SWOT up on garbled agricultural disparity at grassroot levels: A statistical analysis at block levels of Sambalpur district. Int J Stat Appl Math 2022;7(2):68-75. DOI: 10.22271/maths.2022.v7.i2a.811
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