Thanks for the excellent video that illustrates how quasi-Poisson and NB regressions can address over-dispersion. Just a question, is it appropriate to use NB regression when the overdispersion is large and the variance against the mean is about linear?
Hi, can I ask you about the interpretation of the coefficient at the end. The video says it highlights the usage of quasi-poisson and NB model instead of poisson model. Is it because poisson model doesn’t capture the over-dispersed data and includes the intercept as it shows the p-value less than 0.05?
Yes, it is because the Poisson model does not handle over-dispersion, which means that you will violate the assumption of the Poisson model where the variance should be equal to the mean.
Sir i have problem when proofing coefficient in poisson regression and quasi poisson regression are same. Are you have some tutorial to explain why this coefficient between that two models are same?. Can you explain that in mathematic calculation?🙏🙏. Maybe in excel software
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This is the best video about it I have ever seen! Thank you a lot.
Thank you!
Great explanation. Thanks for being "ambassador of statistics" on youtube!
Thank you!
Great video, crystal clear explanations!!
Amazing explanation!
Your explanations are so clear. I found your videos extremely helpful. I wish you success as you deserve to have a few million views soon. :)
Thank you!
Wow, finally i understand the mechanisms behind these regression models. Thank you!
Great!
Thanks for the excellent video that illustrates how quasi-Poisson and NB regressions can address over-dispersion.
Just a question, is it appropriate to use NB regression when the overdispersion is large and the variance against the mean is about linear?
Fantastic! Thank you so much!
Thank you! you solved many questions that I had.
Great!
Thanks for your video!
I have to fit a negative binomial regression and want to calculate R^2. Which R^2 should be used?🙏 thanks in advance!
Destê te sax be ... Thank you very much...
Very well done! Thank you!
Thank you!
Great video omg
Hi, can I ask you about the interpretation of the coefficient at the end. The video says it highlights the usage of quasi-poisson and NB model instead of poisson model. Is it because poisson model doesn’t capture the over-dispersed data and includes the intercept as it shows the p-value less than 0.05?
Yes, it is because the Poisson model does not handle over-dispersion, which means that you will violate the assumption of the Poisson model where the variance should be equal to the mean.
fantastic
Thank you!
Sir i want to ask to you. Is Quasi Poisson regression and Quasi Likelihood regression is different?🙏
I would say that Quasi-Poisson is an example of Quasi Likelihood.
Sir i have problem when proofing coefficient in poisson regression and quasi poisson regression are same. Are you have some tutorial to explain why this coefficient between that two models are same?. Can you explain that in mathematic calculation?🙏🙏. Maybe in excel software