Using the ARIMA Model to Predict the Number of Deaths Classified into Three Age Groups in Diyala Governorate

Abstract

Population societies are affected by vital factors. They increase due to births and decrease due to deaths. The immigration factor also affects the size of the population in two different directions, as the population increases due to the influence of immigration entering the country and decreases due to the influence of immigration leaving the country. The three factors: births, deaths, and migration of both types are the only reasons for the change in the size of the world's population in its various parts and regions. The increasing number of births compared to deaths leads to a net natural increase. Time series are among the most important statistical methods through which it is possible to know the nature of the changes that occur in the values of the phenomenon over time and predict what changes will occur in the values of the phenomenon in the future in light of what happened to it in the past. The most famous modern time series method (Box-Jenkins) is a paradigm shift in data modeling analysis and a modern introduction to time series analysis and forecasting. Death statistics are an essential element in vital statistics and in estimating population numbers and population growth rates. Therefore, the importance lies in building a model used to predict the number of deaths to provide accurate indicators for the planner that will enable him to make future plans. The research dealt with the time series, the components of the series, and the stages of building the Box–Jenkins model, with a practical application of three-time series, represented by deaths of children under one year, deaths of children under the age of five, and total deaths for all of Diyala Governorate, and forecasting the number of deaths during the year 2024