Explaining Parametric Families

An explanation of why parametric families are so commonly used in statistics

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[TriglycerideBeware]

This is my favorite non-entry-level statistics channel. Well done!

[very-normal]

ERRATA (aka my brain on editing)
7:28: Poisson PMF contains the letter "k", but these should all be "x". I let my disdain for the Poisson slip. EDIT: I have no real beef with the Poisson, don’t worry Poisson stans lol

[academyofuselessideas]

The sign of a great presentation is to make explicit what for an expert is obvious! This is important because the expert usually forgets that what is obvious to them is far from obvious to the novice. Thanks for making the concept of parametric distribution to everyone!... Parametric distributions are taught in every basic statistics class, they are so obvious to professors that sometimes they forget to stop a bit and just explain why they are important and what we are doing when we choose a parametric distribution...

In another note, one common mistake is to pick the wrong parametric distribution to model a population... This is one of the main complains about the use of the normal distribution (the classical example is the use of normal distribution in finances which produced misleading estimates of risk during the sub mortgage financial crisis)... But to complement your example on the binomial distribution, it could also happen that each of the trials are not independent

[Matthew-ebdi]

“Stay tuned for a future employee training video on the normal distribution, you’ll be fired if you don’t watch it” 8:58 has me dead 😂

[frankmazza]

I rarely comment on videos, but your channel definitely warrants one. Great work!

[varbias]

Great video! A lot of shade thrown at the Poisson distribution 😅 count data arise all the time in health research and beyond, and the Poisson is (for better or worse) the go-to standard model

[daltakid]

First time seeing the DPQR acronym, very clearly summarized! Perhaps pnorm and qnorm are inverses of each as p and q look to be opposite of each other so easier to remember?

[kprabhakar]

Thank you for great presentation. I learnt a lot from your presentation sir.

[psl_schaefer]

In computational biology the Poisson distribution and the Gamma-Poisson (negative binomial) distribution are used quite often :)

[OhInMyHouse]

So, is it correct to assume that the utilization of the parametric family facilitates the estimation process because we only need to estimate the parameters that shape the function instead of trying to estimate the probability distribution itself because in that case, we would need to estimate a lot of values ?

[plaza]

The chance of a continuous distribution yielding any specific value versus the infinite other possibilities is so unlikely as to be considered 0. Thus, we instead calculate the probability of getting something within a range of values. Meaning that the values that dnorm returns are Not the real probabilities but rather just a y-value from the density function. It's pnorm that calculates the probability of a range, but the first endpoint would need another input, so for convenience we assume the first endpoint is the distribution's minimum. That endpoint makes it identical to the cumulative function. If Rstudio lets you change the first endpoint, then pnorm wouldn't be the cumulative function

[xavierlarochelle]

This is amazing. I want to teach stats one day and I'm definitely gonna steal some ideas from this video. Hope you don't mind! With a proper shout out of course :)

[karansgarg]

Great video! Just pointing out a small typo, @7:28 you've got k instead of x for the Poisson pmf where the function states it's f(x) not f(k)

[yorailevi]

I am mainly waiting for the mode advanced stuff to be covered, like those other distributions mentioned

[braineaterzombie]

Very nice video. Can you please make videos of distributions at 9:14 (not gaussian)in future.

[heyyygrrlitsnina]

Neuroscientists love the poisson distritubution 🥺

[jameyhall]

Good video, but R feels less relevant every year