Open Journal of Statistics

Volume 10, Issue 3 (June 2020)

ISSN Print: 2161-718X   ISSN Online: 2161-7198

Google-based Impact Factor: 0.72  Citations  h5-index & Ranking

Time Series Analysis on Reported Cases of Tuberculosis in Minna Niger State Nigeria

HTML  XML Download Download as PDF (Size: 474KB)  PP. 412-430  
DOI: 10.4236/ojs.2020.103027    50 Downloads   143 Views  


Predicting the trend of non-seasonal data is a difficult task in Social Science. In this research work, we used time series analysis of 144 observations on monthly basis for record of reported cases of tuberculosis patients in Minna General Hospital, Niger State from the period of 2007-2018. Exploratory Data Analysis (EDA: Time Plot and Descriptive Statistics), Stationarity Test (ADF), Trend estimation (Tt), Normality Test, and Forecast evaluation were carried out. The Augmented Dickey Fuller test for stationarity was conducted and the result revealed that the series are not stationary but became stationary after first difference. The correlogram established that the ARIMA (2, 1, 3) was the best model this was further confirmed from the result of L-jung Box. Equation for ARIMA (2, 1, 3) was given as Xt + 0.6867Xt-1 – 0.8859Xt-2 = Et + 1.3077Et-1 - 1.2328Et-2 + 0.5788Et-3. Which was used to predict five years likely cases of tuberculosis in Minna for the period of 2019-2023. It was clearly shown from the projection that the reported cases of tuberculosis reduce year by year by 7% over the period under consideration which could be as a result of intervention from government, health worker, and individuals. In line with these findings, we recommend that the management of general hospital to increase awareness campaign to the public on the causes and dangers of tuberculosis.

Cite this paper

Olanrewaju, S.O., Ojo, E.O. and Oguntade, E.S. (2020) Time Series Analysis on Reported Cases of Tuberculosis in Minna Niger State Nigeria. Open Journal of Statistics, 10, 412-430.

Cited by

No relevant information.

Copyright © 2020 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.