Please use this identifier to cite or link to this item: http://ir.lib.seu.ac.lk/handle/123456789/2340
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dc.contributor.authorFathima Rifka, S.L.-
dc.contributor.authorRazmy, A.M.-
dc.date.accessioned2017-02-14T05:35:05Z-
dc.date.available2017-02-14T05:35:05Z-
dc.date.issued2013-12-03-
dc.identifier.citationSecond Annual Science Research Sessions – 2013 on Exploring Science and Technology For National Development pp.22en_US
dc.identifier.isbn9789556270457-
dc.identifier.urihttp://ir.lib.seu.ac.lk/handle/123456789/2340-
dc.description.abstractRice is the staple food of Sri Lankan. It is cultivated in the whole Island of Sri Lanka. But Sri Lanka imports rice from other countries. Sri Lanka has to maintain selfsufficient in paddy production since Sri Lanka has an experience in export of rice to another nation. It depends on the paddy production model. In literature, most of the authors used time series analysis for paddy production trend and autocorrelation detected from this analysis. The regression Analysis is very familiar and common for trend analysis. This paper analyzes the model of paddy production through Regression Analysis in Sri Lanka. An annually and seasonally forty years (1971 to 2010) of paddy production data of Sri Lanka are used for this Analysis. The outcome of this Analysis can use to calculate of self sufficiency of paddy production and economic growth rate. The conclusion of this study is the production of paddy was increasing over time. Namely; annually, seasonally paddy production was increasing with time but the models of paddy production were different with each other. Annual and Maha seasonal paddy productions are going on a cubic trend and Yala seasonal paddy production model is as a linear.en_US
dc.language.isoen_USen_US
dc.publisherFaculty of Applied Sciences, South Eastern University of Sri lankaen_US
dc.subjectRegressionen_US
dc.subjectAutocorrelationen_US
dc.subjectModelen_US
dc.subjectSelf Sufficiencyen_US
dc.subjectMahaen_US
dc.subjectYalaen_US
dc.titlePaddy production model in Sri Lanka through regression analysisen_US
dc.typeArticleen_US
Appears in Collections:ASRS - FAS 2013

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