STATISTICAL ASSESSMENT OF MODELS FOR DAURO CEREAL CROP

Abstract

Abstract : Statistical tools play greater roles in the assessment of models for all items or variables for the purpose of prediction or drawing inferences about the goods or variables. Leaves, Plant height, Number of tillers, Root, Leaf s area etc are some of the plant attributes that are of great concern to Agricultural researchers because of their immense but varying role they play in plant growth which subsequently affect the plants. In this paper; we wish to establish the best statistical model for Dauro cereal crop considering the plant height, leaf’s areas, number of leaves and number of tiller’s contributions to the model using Ameriya prediction criterium. It was observed that dropping the number of leaves would lead to obtaining the best of the models for Dauro Crop. It was also discovered that the worst model would be obtained when leafs square area was excluded. Thus, the best of the models for Dauro Crop is given by the equation Y = –0.09519 + 0.03125 X1 + 0.000264 X2 + 0.004795 X4 It was also discovered that the worst model would be obtained when leafs square area as plant attributes was dropped. It is therefore significant that when number of tiller is excluded the best model for Dauro crop will be obtained.