Analysis of Teledensity Growth Model Using Augmented Dickey-Fuller Technique (ADFT)

Journal Title: Scholars Journal of Engineering and Technology - Year 2016, Vol 4, Issue 1

Abstract

Abstract: This research developed a teledensity growth model in Nigeria using a multiple regression approach in order to understand the Nigerian telecommunication growth trend for predictive analytics. Data were obtained from four GSM network operators, fixed line operators and CDMA providers. The data used captured number of subscribers and a monthly data summary from February 2012 to January 2013. Using multiple regression technique, an estimating for teledensity growth model was achieved with MATLAB R2011a. The model was tested and validated for prediction and forecasting at a significance level, α=0.05. Advanced Statistical tools like STATASE, Minitab, E-view and Time series analysis were used in this study. Using the Augmented Dickey-Fuller (ADF) test, it was observed that the teledensity time series trend were found to be stationary overtime and had no unit root at second difference. The findings of this study showed that teledensity growth has an increasing trend over time which implies that the linear trend model obtained from the time series regression analysis can be used to make predictions for future behaviour of the process. Hence, six years prediction on the teledensity growth pattern was made and it was found that in the year 2018, that teledensity growth will increase to about 148.4%. Given a population and subscriber base, the model could be applied in any country of the world. Keywords: Teledensity Growth Model, Predictive Analytics, Multiple Regression, MATLAB Software.

Authors and Affiliations

Okafor Chioma Sylvia, H. C Inyiama, C. C Okezie, K. C Okafor

Keywords

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  • EP ID EP383213
  • DOI -
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How To Cite

Okafor Chioma Sylvia, H. C Inyiama, C. C Okezie, K. C Okafor (2016). Analysis of Teledensity Growth Model Using Augmented Dickey-Fuller Technique (ADFT). Scholars Journal of Engineering and Technology, 4(1), 15-24. https://europub.co.uk/articles/-A-383213