Model for Assessment and Computational Analysis of Some Selected Staple Crops in Nigeria

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dc.creatorAliu, T.O.
dc.creator.Obisesan, K.O.
dc.date2019-10-29T05:34:50Z
dc.date2019-10-29T05:34:50Z
dc.date2015
dc.date.accessioned2021-05-05T12:58:49Z
dc.date.available2021-05-05T12:58:49Z
dc.descriptionModel has been derived for assessment and computational analysis of some selected staple crops (maize, rice, beans, yam, and cassava) in Nigeria. Data collected were regressed without data corrected for the mean so that all parameters including the intercept could be obtained from the matrix, so that the variance and co-variances could be easily deduced. The significance of the models and estimated parameters were also analysed using the t-test, Durbin Watson test, Farrar-Glanber test, and Spearman’s Rank correlation coefficient. The results of the analysis shows that the general model: = −1.655 × 10 + 3.231 + 0.644 + 12.328 + 1.366 + 0.356 is found to predict the total output of the selected crops. The model gave rise to a coefficient of determination of 0.986. The results also show that autocorrelation and multicollinearity exists among the explanatory variables, however the variance of the disturbance error term for each of the explanatory variable have no heteroscedasticity. [T.O. Aliu, K.O.Obisesan. Model for Assessment and Computational Analysis of Some Selected Staple Crops in Nigeria. Researcher 2015;7(9):68-71]. (ISSN: 1553-9865). http://www.sciencepub.net/researcher.
dc.formatapplication/pdf
dc.identifierhttp://dspace.cbe.ac.tz:8080/xmlui/handle/123456789/410
dc.identifier.urihttp://hdl.handle.net/123456789/73948
dc.languageen
dc.publisherNational Agency for Science and Engineering Infrastructure
dc.subjectRegression analysis; model; multicollinearity; disturbance error term; heteroscedasticity; staple crops; autocorrelation.
dc.titleModel for Assessment and Computational Analysis of Some Selected Staple Crops in Nigeria
dc.typeArticle

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