Time Series Forecasting Using Arima Methodology with Application on Census Data in Iraq

  • Qais M. Abdulgader Dohuk Polytechnic University
Keywords: Box-Jenkins, ARIMA Models, Time Series Forecasting, Census

Abstract

In this paper, the methodology of Box-Jenkins of Autoregressive Integrated Moving Average (ARIMA) has been used for applying and forecasting the census in Iraq by taking (61) observations of the annually census from 1950 to 2010. Several adequate models of time series have been built and some of the performance criteria have been used for the purpose of comparison between models. Results of the analysis showed that the ARI(2,2) model is adequate to be used to forecast the annually census data of Iraq. During the period 2011 to 2020, there will be (33.58%) increase in the population, and the population of Iraq in 2020 would be (41358200) persons.

Author Biography

Qais M. Abdulgader, Dohuk Polytechnic University

Dept. of Hospital Management, Zakho Technical Institute, Dohuk Polytechnic University, Zakho, Iraq.

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Published
2016-12-30
How to Cite
Abdulgader, Q. (2016). Time Series Forecasting Using Arima Methodology with Application on Census Data in Iraq. Science Journal of University of Zakho, 4(2), 258-268. Retrieved from https://sjuoz.uoz.edu.krd/index.php/sjuoz/article/view/359
Section
Science Journal of University of Zakho