أستعمال بعض طرائق التنبؤ ‏المختلفة لتحليل اعداد المصابين بالاورام الخبيثة

Use of different prediction methods To analyze the numbers of patients ‎with malignant tumors

The huge development in the number of people infected with malignant tumors around the world and the causes of this phenomenon of human and material losses and the effects of social and psychological, including all groups of society the main motive and the main objective we have for the purpose of statistical analysis of this phenomenon and make forecast about the future.

In the theoretical side, some time series methods were used to predict the general linear trend pattern, the quadratic direction model, the non-linear model power (cocave) and the smoothing exponential model in addition to the Box-Jenkins models.

         In the applied side, the methods mentioned in the theoretical side were applied to a sample of 72 people with malignant tumors for the period from 2011 to 2016 according to the months. The results of the statistical analysis found that the series of numbers of patients with malignant diseases in the province of Babylon for the years (2011 – 2016) represent a series of time, not seasonal, which has a general trend, that is an unstable time series, according to the values ​​of the coefficients of self-correlation, the first difference was the most suitable for finding predictions close to the real values. The time square variable in the quadratic model had an adverse effect on the number of people with malignant tumors because its negative sign was estimated at 0.2484 but this effect was slight for the estimated parameter decrease and the growth The ARIMA (1,1،1) model is the appropriate model for predicting the numbers of patients with malignant diseases in Babil Province for the purpose of developing future plans. It has given good predictions and is close to the actual values of the number of casualties, which is illustrated by the real value of 2016, which was used as a control year and in the forecast period.