ABSTRACT

The data used in this study was collected from the Agro Meteorological Office, Agric Engineering Department Owerri, Imo State.we are concerned with the analysis of date, diagnostic check for model accuracy, chi-square test for model accuracy, derivation of model equation and forecasting. This method of analysis of the data was time series analysis, MINITAB was employed in fitting the model that was capable of explaining some properties of the original data In doing this, the original data was not stationary but there was no seasonal component. Since there was no cut off at the lags, the data was differenced and the data became stationary Stationary time series implies that the series contained no trend and seasonal variation. Thereafter, based on the diagnostic check tools, the (ACF) Auto Correlation Function and the (PACF) Partial Auto Correlation Function graphs, the ARIMA model (Auto Regressive Integrated Moving Average) was identified. The appropriate model was identified. This identified model was used to forecast the future monthly rain fall values Finally, based on the result of analysis, conclusions were drawn and recommendations were made which can be of great benefit to farmers in owerri zone, Government and Health officers