HR Hypothesis Testing

PART 1

PART 2

• Q2.1: The sample mean of MonthlyIncome for the cleaned dataset is approximately $5,502.76.​

• Q2.2: The p-value for this two-tail test is approximately effectively 0.​

• Q2.3: Since the p-value (≈ 0) is far less than α = 0.05, reject H₀. Conclusion: There is statistically significant evidence that our company's average monthly income is different from the national average of $6,200. Specifically, our average ($5,503) is significantly lower.

PART 3

• Q3.1: The sample proportion of attrition is approximately 0.1711.​

• Q3.2: Since this is a one-tail test , divide by 2: the one-tail p-value is approximately 3.34 × 10⁻⁷.​

• Q3.3: Since the one-tail p-value (≈ 0.000000334) is far less than α = 0.05, reject H₀. Yes, there is strong statistical evidence that our company's attrition rate (17.1%) is significantly greater than the industry baseline of 12%. The HR Director has reason to be concerned.

PART 4

• Q4.1: Research & Development had the highest raw count of "Yes" for Attrition with 130 employees leaving. Sales may have a higher rate of attrition, R&D has the highest count because it is the largest department.​

• Q4.2: Chi-Square statistic ≈ 9.84, degrees of freedom = 2, p-value ≈ 0.0073.​

• Q4.3: Since the p-value (0.0073) is less than α = 0.05, reject H₀. "There is a statistically significant relationship between department and attrition. Employee turnover is not evenly distributed — the department someone works in does affect their likelihood of leaving."