Assumptions in Linear Regression - explained | residual analysis
www.tilestats.com/
1. How a residual plot is created
2. Linear relationship (03:07)
3. Equal variance - homoscedasticity (04:44)
4. Normality (06:50)
5. Cook's distance (09:30)
6. Independence (11:48)
7. No collinearity - variance inflation factor (13:33)
Пікірлер: 12
amazing video. I really like how you use arrows, lines and boxes in your video, which helps form a picture in my head and helps me understand difficult and abstract concepts
Excellent video, so really help
Excellent video! Thank you!
you clarified so much!
Thanks for video and really help me to break stat model
Plz continue with your content, is really cool, congrats
Excellent!
This is so helpful, would you please clarify why the unequal variance will lead to a smaller p value?
It was again another clear and explanatory video by Tileststs. I wonder if you can kindly provide a video with hand calculations on differences between various types of Anova (Type I, Type II and Type III) and their applications? There was an explanation here(link below), but not a very clear one. Many thanks
@tilestats
Жыл бұрын
The last videos in this playlist show how to calculate a 2way ANOVA by hand and discuss type 1-3 models: kzread.info/head/PLLTSM0eKjC2dvba2A0VCUogEGDch6cXFN
Excelente
thank you!