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

Qais M. Abdulgader(1)
(1) Dohuk Polytechnic University

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.

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Authors

Qais M. Abdulgader
juoz@uoz.edu.krd (Primary Contact)
Author Biography

Qais M. Abdulgader

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

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

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How to Cite

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

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