Statistical Assessment of Employee’s Turnover and Its Causes; In the Case of Moret and Jiru Wereda, North Shoa, Amhara, Ethiopia
American Journal of Theoretical and Applied Statistics
Volume 7, Issue 4, July 2018, Pages: 139-146
Received: Mar. 17, 2018; Accepted: Mar. 30, 2018; Published: May 3, 2018
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Author
Natnael Mamuye, Department of Statistics, College of Natural and Computational Science, Debre Berhan University, Debre Berhan, Ethiopia
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Abstract
The purpose of this study is to assess the employee turnover rate and cause in the case of Moret and Jiru Wereda. In light of this objective the study adopted quantitative and qualitative method of research approaches to test a series research hypothesis and subjective analysis respectively. Specifically, the study used survey of questionnaire analysis of Moret and Jiru Wereda. 326 respondents were selected based on stratified random sampling method. Data was then analyzed on quantitative basis using binary logistic regression and descriptive statistics; however, qualitative basis was used to subjective data. The result of this paper indicates that among the respondents 39.9 % of them do not want to quit their current job but majority of them (60.1%) said they seriously consider quitting their job very often. And furthermore the logistic regression found that Age of respondent, income of the respondents, experience of the respondents, educational level, satisfaction and incentive to be significantly related with turnover intension of the respondents and other factors such as gender, working hour and stress are found to be insignificant predictors of the turnover intension of the employees.
Keywords
Moret and Jiru Wereda, Turnover Intension, Logistic Regression
To cite this article
Natnael Mamuye, Statistical Assessment of Employee’s Turnover and Its Causes; In the Case of Moret and Jiru Wereda, North Shoa, Amhara, Ethiopia, American Journal of Theoretical and Applied Statistics. Vol. 7, No. 4, 2018, pp. 139-146. doi: 10.11648/j.ajtas.20180704.12
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Copyright © 2018 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.
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