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OLS. R and Python. In this project, we study fundamental concepts of Supervised ML models, such as Regression Analysis: Coefficient of Model Adjustment (R²), Parameters Estimation ,Statistical Significance of the Model (F test, T test) ,Multiple Regression , Qualitative Explanatory Variables (X) , heteroscedasticity and etc.

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GLM		GLM
Non-LinearModels		Non-LinearModels
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README.md		README.md

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Supervised-ML

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OLS. R and Python. In this project, we study fundamental concepts of Supervised ML models, such as Regression Analysis: Coefficient of Model Adjustment (R²), Parameters Estimation ,Statistical Significance of the Model (F test, T test) ,Multiple Regression , Qualitative Explanatory Variables (X) , heteroscedasticity and etc.

statistical-analysis t-test parameter-estimation non-linear-regression supervised-machine-learning regression-analysis f-test non-linear-model general-linear-models dummy-variable

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