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2. Assumptions of OLS Regression

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2. Assumptions of OLS Regression

The lecture covers theory around assumptions of OLS Regression on Linearity, Collinearity, and Errors distribution. The lecture covers concepts such as homoscedasticity, heteroskedasticity amongst errors and the requirement of errors to be iid i.e. independent and identically distributed. An understanding of basic statistics including ...

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