A Model Selection on Economic Variable in Nigeria
Biomedical Statistics and Informatics
Volume 1, Issue 1, December 2016, Pages: 13-18
Received: Sep. 11, 2016;
Accepted: Oct. 21, 2016;
Published: Dec. 12, 2016
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Muritala Abdulkabir, Statistics Department, Lens Polytechnic Offa, Offa, Nigeria
Omuku Ikechukwu Joshua, Statistics Department, Lens Polytechnic Offa, Offa, Nigeria
Raji Surajudeen Tunde, Mathematics and Statistics Department, Federal Polytechnic Offa, Offa, Nigeria
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This study is on model selection on economic variable on gross domestic product in Nigeria, the data used for this study were extracted from National Bureau of Statistics (NBS), the statistical tool is multiple regression model and model selection to select the best model and in the variable and to evaluate and test GDP as a determinant which will capture the effect on economic variables. At the end of the analysis and findings it were concluded that Import value import value from the export, production, petroleum and consumption plays the most significant role in the company’s market. It can be used as a tool to estimate the company’s future market price.
Gross Domestics Product, Multiple Regression, Model Selection, Variance Inflation Factor (VIF), Tolerance
To cite this article
Omuku Ikechukwu Joshua,
Raji Surajudeen Tunde,
A Model Selection on Economic Variable in Nigeria, Biomedical Statistics and Informatics.
Vol. 1, No. 1,
2016, pp. 13-18.
Copyright © 2016 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/
) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abiola, J., & Asiweh, M. (2012). Impact of tax administration on government revenue in a developing economy- a case study of Nigeria. International Journal of Business and Social Science. 3(8), 99-113.
Afuberoh, D., & Okoye, E. (2014). The impact of taxation on revenue generation in Nigeria. A study of Federal Capital Territory and selected states. International Journal of Public Administration and Management Research. 2(2), 22-47.
Ayuba, A.J. (2014). Impact of non-oil revenue on economic growth: the Nigerian perspective. International Journal of Finance and Accounting. 3(5), 303-309. Berman, H. (n.d.). Residual Analysis in Regression. Stat Trek. Retrieved from http://stattrek.com/regression/residual-analysis.aspx
Douglas Montgomery, Peck, E., & Vinning, G. (2012). Introduction to Linear Regression Analysis (5th ed.). Wiley. Experiment Design and Analysis Reference. (n.d.). ReliaSoft. Retrieved from http://reliawiki.org/index.php/Experiment_Design_and_Analysis_Reference
Iyanaga, S., & Kawada, Y. (1980). Statistical Estimation and Statistical Hypothesis Testing. (Vol. Appendix A, Table 23). Cambridge, MA: MIT Press.
Otu, O. H., & Adejumo, T. O. (2013). The effects of tax revenue on economic growth in Nigeria (1970-2011). International Journal of Humanitiesand Social Science invention. 2(6), 16-26.
Edame, G. E., & Okoi, W. W. (2014). The impact of taxation on investment and economic development in Nigeria. Academic Journal ofInterdisciplinary Studies. 3(4). 209-218.
Fasoranti, M. M. (2013). Tax productivity and economic growth. Lorem Journal of Business and Economics. 1(1), 1-10.
Okoye, P.V.C., & Ezejiofor, R. (2014). The impact of e-taxation on revenue generation in Enugu, Nigeria. International of Advanced Research. 2(2), 449-458.
Residual Analysis. (n.d.). DePaul University. Retrieved from http://facweb.cs.depaul.edu/sjost/csc423/documents/resid-anal.htm