International Journal of Statistics and Applied Mathematics
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2019, Vol. 4, Issue 4, Part A

Multiple regression model fitted for job satisfaction of employees working in saving and cooperative organization


Author(s): Ramesh Prasad Tharu

Abstract: The research study aims to identify the significant factors affecting job satisfaction of employees working in saving and cooperative organization in Nepalgunj sub-metropolitan city of Bank District, Nepal; with the help of multiple linear regression model. This study has applied a cross-sectional and descriptive statistical research designs entirely based on primary data. A representative sample of size 161 was collected by using a structured questionnaire to each employee. F-ratio’s have been calculated to test the overall significance of the coefficients of fitted multiple regression model (i.e. to test the goodness of fit of the multiple regression model). The fitted multiple linear regression model has shown that the factors pay facilities, working environment, training courses, encouragement factors and motivation factors have significant impact on job satisfaction of the employees under the study. The findings reveal that all the significant variables have positive impact on job satisfaction. Although, the variables like supervision, relationship with co-employees and carrier development opportunities are not significant in the final model but it is important variable and is significant while correlating with job satisfaction.

Pages: 43-49 | Views: 1782 | Downloads: 392

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International Journal of Statistics and Applied Mathematics
How to cite this article:
Ramesh Prasad Tharu. Multiple regression model fitted for job satisfaction of employees working in saving and cooperative organization. Int J Stat Appl Math 2019;4(4):43-49.

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