<![CDATA[Climate change has serious effects on human life and existence in various forms. This study used Principal Component Analysis (PCA) and Mutiple Regression model (MRM) to determine the effects of meteorological factors and socio-economic factors on agricultural production. PCA showed 95.6% aggregated variation within the variables and the correlation matrix of the principal components was used to reduce the variables to six. MRM was employed for determining linear association within agricultural productions and the reduced factors showed that climate change and socio-economic factors influenced Nigerian agriculture production. The model obtained was validated with respect to coefficient of determination, adjusted coefficient of determination and Durbin Watson statistics values. Overall, this study indicated that climate change and socio-economic factors influenced the level of agriculture productions in Nigeria.]]>
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