Regression Analysis is an analytical method where a series of input variables are examined in relation to their corresponding output results in order to develop a mathematical or statistical relationship.
This method is used to predict outcomes, evaluate trends, and quantify the influence of specific factors on project performance.
Key Characteristics
- Quantitative Technique – Applies mathematical modeling to historical data
- Identifies Relationships – Examines correlations between variables and outcomes
- Supports Forecasting – Projects future performance based on past behavior
- Used in Cost and Schedule Estimating – Enhances accuracy of predictions
Example Scenarios
- Using historical project size and team hours to predict future labor needs
- Analyzing cost drivers across similar projects to refine budget estimates
- Evaluating the impact of design changes on delivery timelines
Role in Performance Analysis
- Improves Estimate Accuracy – Refines predictive models using real project data
- Enables Data-Driven Decisions – Supports objective planning and control
- Enhances Root Cause Analysis – Clarifies drivers behind variances
- Strengthens Performance Measurement – Links inputs to outputs for better oversight
See also: Trend Analysis, Forecasting, Earned Value Management, Performance Reviews, Variance Analysis.