this what i found:Data Analysis and Research Findings The dataset included 1,000 employees with a near-even gender split (52% male, 48% female). The average age was 42 years, and employees had an average tenure of 4.5 years. Job satisfaction scores ranged from 1 to 6, with a mean of 4.6 and a standard deviation of 1.2, indicating moderate variability. Absenteeism showed significant variation, with an average of 12.46 absent days per year and a high standard deviation of 38.93, suggesting extreme outliers. These descriptive statistics provided a baseline understanding of workforce trends, highlighting that while job satisfaction was generally moderate, absenteeism varied widely. Pearson's correlation analysis revealed a statistically significant negative relationship (r = -0.32, p < 0.01) between job satisfaction and absenteeism. This supported Hypothesis 1 (H1), confirming that employees with higher job satisfaction tended to have fewer absent days. The moderate strength of the correlation suggested that while job satisfaction was an important factor, other variables also influenced absenteeism. This finding aligned with prior research (Bell & Harley, 2023), reinforcing that improving job satisfaction could reduce organizational absenteeism rates. A linear regression model tested the predictive power of job satisfaction on absenteeism while controlling for tenure and age. Job satisfaction had a significant adverse effect ( = -0.28, p < 0.01), meaning each one-point increase in satisfaction reduced absenteeism by 0.28 days. When tenure and age were added, the relationshi