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Regression: Identify Assumptions & Apply Models

Курс от Coursera

Средний≈ 3 чАнглийский

О курсе

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.

Навыки, которые вы освоите

R Programming Statistical Analysis Regression Analysis Model Evaluation Statistical Methods Technical Communication Predictive Modeling Statistical Modeling Forecasting Financial Forecasting Reliability Statistical Reporting Statistical Programming Variance Analysis Verification And Validation Data Presentation Plot (Graphics)

Программа курса

1 модулей · 16 учебных материалов

01Regression: Identify Assumptions & Apply Models16 материалов

Understanding Regression Assumptions: The Hidden Rules Behind Reliable Models

When Have You Skipped a Check?DIALOGUE Welcome: Why Regression Assumptions MatterВидео The Four Regression Assumptions ExplainedВидео Diagnosing Before Modeling: Understanding Classical Regression AssumptionsЧтение

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