A Study on a Job Stress Evaluation Methodology using data mining and RSM

Job stress is caused by a poor match between us and our complicated condition that can be classified with physical, psychosocial and environmental factors. While a factor analysis and management policy conduct through a survey research which is used to study job stress problem mostly, there are limitations such as dimensionality associated with large data set of stress factors problem. In order to address the limitations on the data computing and analysis capabilities, we propose an advanced survey analysis procedure incorporating Data Mining (DM) into a statistical analysis, and provide detailed statistical relationships among the factors and interesting responses by utilizing Response Surface Methodology (RSM). The objective of this research is to show how DM techniques can be effectively applied into a survey analysis related to a job stress evaluation by applying a correlation-based feature selection (CBFS) method.