R-squared (R²), also known as the coefficient of determination, is a key metric in regression analysis that indicates how well a model explains the variability of the target variable. Whether you’re working in data science, economics, or academic research, understanding R² is crucial for evaluating how well your model fits the data.
On R-Quadrat.info, we provide in-depth explanations of R², from basic interpretations in linear regression to more advanced applications like adjusted R² and R² in non-linear models. We also explore common misconceptions, how to interpret low vs. high R², and what it means in real-world prediction scenarios. Each article includes formulas, visuals, and Python examples to help you apply theory in practice.
Explore our tutorials, compare models, and build confidence in your analytical skills. R-Quadrat.info is designed for students, analysts, and researchers seeking clarity in model evaluation. Learn how to measure accuracy — and understand what your regression results really mean.