From the course: Practical Python for Time Series Analysis

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Robust regression

Robust regression - Python Tutorial

From the course: Practical Python for Time Series Analysis

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Robust regression

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- [Instructor] After calculating the residuals and interpreting how the model works, now we are ready to go into the the diagnostics and assumptions, which are checks that you perform, above all on the residuals. From the result we obtained, the last element, which is a table with the kurtosis, skew, omnibus, we are getting the results of statistical tests to validate some of these assumptions, but I have put the most important ones in the table of content of this notebook, that one is homoscedasticity and linearity, another one is the normality of the residuals and the independence of the residuals. For each one of these tests, there are two parts. One is first two plots, which are the variables to contrast based on the results of the model, and then the statistical test to see if there are significant differences on the comparison for the assumption. Why all of this is important? Because the results that we get in our…

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