This project evaluates the financial impact of a workplace wellness programme using data from a randomised control trial (RCT). The analysis begins by cleaning the dataset and renaming variables for clarity. It then explores the data through summary statistics and visualisations, highlighting a potential selection bias where healthier employees are more likely to enrol. To address this, the study contrasts a standard OLS regression, which misleadingly suggests cost savings due to the "healthy user" effect, with an instrumental variables (IV) regression. The IV analysis uses the random assignment of the programme as an instrument to isolate the true causal effect, ultimately revealing that the wellness programme has no statistically significant impact on reducing employee medical spending.

This comprehensive analysis follows the CRISP-DM (Cross-Industry Standard Process for Data Mining) methodology to investigate factors affecting mathematics performance in Ekiti_schools. i examined six specific research questions using both descriptive and inferential statistics approaches to understand the relationships between continuous assessment frequency, demographic factors, and mathematics unified examination scores in Ekiti_State.