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     Research Journal of Mathematics and Statistics


Mean Vector Analyses of the Voting Patterns of Ghanaians for Three Consecutive Periods: A Case Study of the Greater Accra Region

R. Opoku-Sarkodie, S. Amponsah Gyimah, F. Gardiner and T. Manu
Methodist University College Ghana, Dansoman, Accra, Ghana
Research Journal of Mathematics and Statistics  2014  3:30-34
http://dx.doi.org/10.19026/rjms.6.5269  |  © The Author(s) 2014
Received: June ‎08, ‎2014  |  Accepted: August ‎19, ‎2014  |  Published: August 25, 2014

Abstract

The aim of this paper was to find out whether the outcome of future elections in the Greater Accra region could be predicted based on empirical data. The voting patterns of the presidential elections in Ghana deserve notice, not because of their political significance but because of the theoretical weight they carry. The shifts in electoral fortunes between the two main political parties in the country, especially in the greater Accra region provide a unique leverage for assessing theories of voting behavior. The paper uses statistical tools to examine the electoral performance of the four major political parties in Accra and the Hotelling’s T2 Statistic to test whether a prediction could be made to predict future outcomes of elections. Our results revealed that there was not enough statistical evidence to predict future outcomes of elections in the greater Accra district.

Keywords:

Mean vector, multivariate analysis, voting patterns,


References


Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.

ISSN (Online):  2040-7505
ISSN (Print):   2042-2024
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