The Forecasting Model of the Probability of being Happy Staff in Faculty of Science, Prince of Songkla University in 2018

Abstract

The research aimed to measure the level of happiness of staff in the Faculty of Science, Prince of Songkla University and build the forecasting model to predict the probability of being happy or unhappy for this population. Population is 369 staff in the Faculty of Science. Data were collected from both academic and support staff using convenience sampling method (n=176) between January and March, 2018. The Frequency percentage and mean were used to measure the level of happiness of staff. The forecasting model was constructed using logistic regression analysis.

The results showed that most respondents (56.8%) reported the levels of happiness at the level of fairly to very happy. In addition, when examining the 9 paradigms associated with levels of happiness, having good health was mostly reported at the level of fairly to very happy (74.3%). However, the paradigm of having good relaxation was mostly reported to be at the level of fairly to very unhappy (69.9%). Furthermore, the reinforcing factors of being happy in the cohort were good relaxation, good family, good caring, good financial status, good health, good ambition, and good mental health. As such, the forecasting model of the probability of being happy was described as

when represents being happy (unhappy (0) / happy (1) /Z = -11.726 + 4.274(good relaxation) +3.432(good family) + 3.310(good caring) + 3.257(good financial status) + 2.585(good health) + 2.562(good ambition) + 2.160(good mental health)

The percentage accuracy in classification is 89.