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Regression Analysis

A quantitative method that studies how one or more input variables relate to an outcome variable and derives a statistical equation that explains and predicts that relationship.

Key Points

  • Examines independent (input) variables against a dependent (output) variable to quantify their relationship.
  • Produces coefficients and fit metrics (for example, R-squared) that support prediction and forecasting.
  • Can be simple (one predictor) or multiple (many predictors), and may use linear or nonlinear forms.
  • Relies on quality historical data; check assumptions, manage outliers, and remember correlation is not causation.

Example

A construction project team analyzes past jobs where inputs were square footage, number of floors, and material grade, and the output was total cost. They fit a regression model to estimate cost for a new building based on its planned size and complexity.

PMP Example Question

During estimating, the team analyzes historical data on number of features, code complexity, and team experience to quantify their effect on testing effort and to build an equation that predicts future testing hours. Which technique are they using?

  1. Analogous estimating
  2. Regression analysis
  3. Critical path method
  4. Monte Carlo simulation

Correct Answer: B — Regression analysis

Explanation: Regression analysis develops a statistical relationship between multiple inputs and an output to create a predictive equation.

Advanced Lean Six Sigma — Data-Driven Excellence

Solve complex problems, reduce variation, and improve performance with confidence. This course is designed for professionals who already know the basics and want to apply advanced Lean Six Sigma tools to real business challenges.

This is not abstract statistics or theory-heavy training. You’ll use Excel to perform real analysis, interpret results correctly, and apply tools like DMAIC, SIPOC, MSA, hypothesis testing, and regression without memorizing formulas or relying on expensive software.

You’ll learn how to measure baseline performance, analyze process capability, use control charts to maintain stability, and validate improvements using statistical evidence. Templates, worked examples, and structured walkthroughs help you apply each concept immediately.

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Advance your Lean Six Sigma expertise!

HK School of Management helps you take Lean Six Sigma to the next level—without the overwhelm. Master advanced statistical tools, Excel-based analysis, and real-world improvement techniques to solve complex problems with confidence. For the price of lunch, you get practical templates, guided examples, and hands-on project experience you can use immediately at work. Backed by our 30-day money-back guarantee—zero risk, real impact.

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