Regression Assumptions and Model Application

Learn how to make your regression models trustworthy, not just accurate. In this short, hands-on course, you'll explore the key assumptions behind classical linear regression and practice verifying them in RStudio. You'll fit an Ordinary Least Squares (OLS) model, visualize residuals, and detect patterns like heteroscedasticity that can distort financial forecasts. With guided discussions, a coding lab, and diagnostic interpretation, you'll build the confidence to present reliable, evidence-based results. By the end, you'll know how to test assumptions, interpret residuals, and communicate findings clearly to both analysts and decision-makers

• Ensure regression models are trustworthy, not just accurate
• Explore key assumptions behind classical linear regression
• Practice verifying assumptions using RStudio
• Fit Ordinary Least Squares (OLS) models
• Analyze residuals and detect heteroscedasticity
• Communicate evidence-based findings clearly

• Basic familiarity with the topic and its common terminology
• Readiness to practice through applied exercises or case-based work