Please use this identifier to cite or link to this item: http://repository.futminna.edu.ng:8080/jspui/handle/123456789/16766
Title: Constructing the Best Regression Model for Maiwa Variety
Authors: Abdullahi, F. Busari
Abubakar, Usman
Cole, A. T.
Keywords: Regressor, predictor, goodness-of-fit, multivariate, yield, tiller
Issue Date: Apr-2010
Publisher: Pakistan Journal of Nutrition
Series/Report no.: 9;4
Abstract: As difficult as it can be to determine the plant attribute that contributes most to better yield of cereal crop named Maiwa. We use multivariate regression model to determine the contribution of Plant height (X1); Number of leaves (X2); Numbers of tillers (X3) and Leaf’s area in square feet (X4). Four multivariate regression models were developed by dropping each attribute. A data set collected from the Institute of Agricultural Research (IAR) Ahmadu Bello University, Samaru-Zaria was used for the analysis. Using each of the models to assess the contribution of each attribute, it was discovered that the Multivariate regression model that has the best fits of the data set, when covariates are dropped one after the otheris Y=0.02371 -0.003111X2 +0.001759X3 - 0.002503X4 . Thus, the plant height (X1) is an irrelevant plant attrbute for the variety-Maiwa.
URI: http://repository.futminna.edu.ng:8080/jspui/handle/123456789/16766
ISSN: 1680-5194
Appears in Collections:Mathematics

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