In this paper, two separate exploratory analysis procedures are employed and contrasted. They are: Data Mining and Linear Regression. The specific Data Mining technique used is Decision Tree analysis. By employing the two techniques this paper illustrates how results from Linear Regression and Data Mining differ can differ, and how they can complement each other.
Exploratory data analyses are conducted on data obtained from a survey of Developers (computer programmers). The response variable in the model is Job Satisfaction. Exploratory analyses are conducted using five variables as possible predictors. These are Age, Length of Current Work Experience, Employment Status, Compensation, and Remote Work Status.
The Linear Regression model identifies Age, Compensation and ability to do Remote work as drivers of Job Satisfaction. Decision Tree analysis identifies high Compensation and ability to do Remote work as factors that result in Developers loving their jobs.
software developer, job satisfaction, comparision