Your videos are always sooo helpful and make the topic simplified. This really helped me on my homework in Georgia Tech Linear Reg class...thank you!!!
Wow Nice to watch and learn by Prof. Mike Marin, a distinguished teaching! I Always watching and learn from your videos from Ethiopia! Wish you all z best!
Can you kindly add the Overdispersion and excessive zeroes and two Part videos of Poisson regression of Mary Clare Kennedy also a part of the video lecture series of Poisson regression then it will be helpful for viewers.
If in reality the variance is larger than the mean. Not the parameters used in the model. The model only estimates the mean (lambda) and then assumes this value for the variance as well. If in reality the variance is larger than the value assumed for it (lambda)
Your videos are always sooo helpful and make the topic simplified.
This really helped me on my homework in Georgia Tech Linear Reg class...thank you!!!
This has been the most helpful video for my question in my statistics class. Thank you!
Wow Nice to watch and learn by Prof. Mike Marin, a distinguished teaching! I Always watching and learn from your videos from Ethiopia! Wish you all z best!
Thank you so much for the excellent teaching.
Thank you for this! I needed this information today! Very helpful.
Very helpful thanks very much!
You are an excellent teacher!
That intro has me conditioned to expect:
"So, you have a new regression technique for me?"
What about quasipoisson?
These videos are very helpful and I'm enjoying them . but, I think it would be fair to place the videos in order.
They are in order, just view through the playlist and they will all be in order
Can you kindly add the Overdispersion and excessive zeroes and two Part videos of Poisson regression of Mary Clare Kennedy also a part of the video lecture series of Poisson regression then it will be helpful for viewers.
All of the tutorial videos in the series are there
So how exactly can the variance be larger than the mean if they use the same parameter lambda with the same value? This doesn't make sense...
If in reality the variance is larger than the mean. Not the parameters used in the model. The model only estimates the mean (lambda) and then assumes this value for the variance as well. If in reality the variance is larger than the value assumed for it (lambda)
Why I dont have this lecturer in my Uni. I all have lecturers readings slides.
thank you a lot, tomorrow exam :)