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esosetrov / ordinary_least_squares

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A complete guide to Ordinary Least Squares regression with diagnostics, robust alternatives, and best practices. Includes theory, implementation, model comparison, and practical recommendations using Python's statsmodels.

modeling linear-regression p-value statistical-analysis statistical-inference autocorrelation polynomial-regression multicollinearity coefficient-estimates regression-analysis heteroscedasticity residual-analysis model-diagnostics statmodels durbin-watson ordinary-least-square-regression homoscedasticity jarque-bera-test r-squared-statistic
  • Updated Apr 3, 2026
  • Jupyter Notebook

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