Poisson regression - clearly explained

In this first video about Poisson regression, we will see:
1. How the Poisson regression differs from linear regression.
2. How to interpret the coefficients from a Poisson regression model (8:34)
3. How to calculate and interpret the incidence rate ratio (IRR) (13:48).

[XtremeTerror]

Better and easier explanation than most statistic books. Great job!

[zerdofish]

This made the concept click in my brain. Best video on the topic out there

[MononeRocks]

Very clear explanation! Thanks for the illustrations and the great examples!!!

[cristinasalvatori]

best tutorial on poi regression ever. I wished you explained also the poi regression with multiple explenatory variables. That would have been awesome. Thank you so much this helped me wiht my statistics assignment!

[exarchoskanelis]

finally a good video, i tried so many videos to understand GLMs and Poisson.... thank you!

[mikahamari]

Great explanation with simple example, and simple in tutorial means perfect. Thank you!

[aogreaves]

this really clicked with me, thank you! seconding the request for gamma regression

[haitrieuphan]

This lecture is very helpful. I am looking forward to the next.

[penthing]

You are saving my life. I'm implementing one for a bayesian statistics class and got kind of lost at some point. Thanks!

[SamuelDevdas]

Please write an end to end to end Stats + Machine Learning book! Will definitely buy!

[mustafeibrahim-xxfk]

great explanation, I have one comment, in the graph in the X axis you wrote week, better to say weeks because you are dealing different weeks, not single week. statistic beginners may confuse it.
thank you and keep up your efforts.

[farmzr]

crystal clear, thanks! great job, though I will have to re-watch the last 3mins... too many "logs" at some point, can be a bit of overkill being confronted with multiple logs / e to power of... within a sentence ... for ppl that are not so familiar with logs. not that I'm completely unfamiliar with it, but it s not as crystal clear as "mean" etc. in my head, always takes a bit to process it

[riesenpurzel]

how exactly would I calculate the skewed poisson distributed variance that is talked about in 5:00 onwards (for example for calculating non-symmetric confidence limits?

[danielping]

thank you ! how do we evaluate the overall fit of the model ?

[গোলামমোস্তফা-শ৮থ]

But why call it poisson regression where the graph you used is clearly follows a exponential distribution?

[ΔημητρηςΠαπαγεωργιου-γυ]

Why assume a normal distribution in the error terms of the exponential model and not an exponential distribution which still doesn't allow negative values and the variance is a function of the mean like in poisson?

[syphiliticpangloss]

You are missing the lambda ^ k term everywhere?

[AbdulHafeez-zitd]

Kindly make video on gamma regression, ridge, lasso, elastic net, bayesian regression, orthogonal regression, quantile regression, weighted regression,

[tonycardinal]

Very good. But why are you making things more complicated than they are? At about 13 minutes in you talk about "multiplicative factor" and use it to predict the counts. Why not just plug in the value of x into the original formula (e^(4.605 - .418 x)). This will get you the number of counts for a given week x. Musch more straight forward, much more intuitive, and more direct. Maybe I'm missing why you did it the other way. It kind of threw me off doing it your way. But thanks for the video