C207 Task 1 Linear Regression Analysis | WGU Nurse Attrition Study

This task submission provides a complete linear regression analysis for C207 Data‑Driven Decision Making at Western Governors University (WGU). It focuses on the relationship between nurse attrition rates and participation in employee well‑being programs. Key areas include: Business scenario: Evaluating whether program participation reduces nurse attrition and turnover. Null hypothesis: No significant relationship between participation rate and attrition rate. Analysis technique: Linear regression chosen for one independent variable (program participation rate) and one dependent variable (nurse attrition rate). Data details: 36 months of data, 72 data points, ratio scale measurements. Results: R² = 0.7484 showing a modest fit. P‑value = 1.01252E‑11, statistically significant, rejecting the null hypothesis. Linear equation: y = -0.0815x + 5.2683, useful for predicting future attrition rates. Limitations: Only two variables analyzed; other factors like hours worked, salary, and environment not included. Recommendations: Continue the well‑being program, analyze annually, and expand variables to improve accuracy. This task demonstrates how linear regression can guide HR decisions, reduce nurse turnover, and improve organizational efficiency. It is ideal for WGU students completing C207 Task 1 and learning applied statistical methods in business contexts.