Checking The Assumptions Of Linear Regression | Statistical And Visual Methods | Part 2

🔥 In this video, we provide the methods for checking the assumptions of linear regression. As mentioned by our latest video, there are four main assumptions of linear regression: Linearity, Independence, Homoscedasticity and Normality. We provide one statistical and one visual way for inspecting each of the assumptions.

Tests and methods used in the video for identifying the assumptions are the following:

Residuals vs. Fitted Values plot, Autocorrelation Function Plot (ACF), QQ-Plot, Histogram, Rainbow Test, Ljung-Box Test, Breusch-Pagan Test, Shapiro-Wilk Test.

The video is introductory. If you wish to learn deeper about each method, tell us in the comments section!

🔍 Key points covered:

0:00 - Introduction.
0:08 - How to check linearity? (Visual method)
0:21 - How to check linearity? (Statistical method)
0:51 - How to check Independence? (Visual method)
1:06 - How to check Independence? (Statistical method)
1:18 - How to check Homoscedasticity? (Visual method)
1:34 - How to check Homoscedasticity? (Statistical method)
1:57 - How to check Normality? (Visual method)
2:11 - How to check Normality? (Statistical method)
2:23 - Subscribe to us!

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