Explaining Probability Distributions 

The place where you link Probability with Statistics is really good.. It's really helpful to make a picture about the things you deal with in your daily work.

Good thing it's Sunday. Professional relaxers only. We can never be fired.

I love your way of introducing concepts. I am a Comp Sci. student currently getting into medicine and those videos are insanely helpful. Looking forward to your more advanced videos

This was great! Having done some self-study on statistics in the past year, these videos are great for re-stimulating all the connections and also seeing some familiar concepts in a new light.

Great explanation! This really helped me put all these concepts together.

Great video, thanks for your work! really clear and polish explanations

Grateful to you ;as a grad student very helpful for me as a refresher video to go through

This video is pure gold

Love your channel! Thank you so much!

It was helpful, thanks for creating it.

great video, brilliant!

loved this one

The best statistics channel ❤❤❤

I think “T” is used because it stands for “Test Statistic”. That is, the reason we’d be interested in a statistic is because of its distribution which would be related to figuring out how interesting the value of it is under our distributional assumptions. That, or it stands for the “t” in statistics since “s” is already used for standard deviation and sometimes sum.

great content. yet another banger. ✨

To complement your discussion on probability vs statistics, one can think of Probability as knowing the data generating process and studying the properties of the data generated by it, and of Statistics as knowing the data and studying the properties of the data generating process that could have generated it

Subscribed and liked.

I found your channel and I feel like I find a gold mine. Hey, could recommend some books or resources for a beginner in stats .

In 5:21 I believe there is an error. A Probability distribution actually has a formal definition (see e.g. en.wikipedia.org/wiki/Probability_distribution#Kolmogorov_definition). It has to be a Probability Measure, implying that the function's domain is [0,1], (also its codomain is a sigma-algebra, so each input is a set...) and the result is a probability. If you plug in half-open intervals (-∞, x] to a probability distribution, you get the cdf. This distinction is actually important because there are discrete RVs, which have a probability mass function (pmf), and continuous RVs, which have a probability density function (pdf), but - and this is where it is relevant - there are also mixed RVs, that are described by neither. This is a pain to deal with if you want to write a general form for anything - for instance an expected value. Still, with a little measure theory (and I mean really little, I hardly know any of it myself...) it is possible to generalise...

Nice video and example. On the r example part I have one question though. Why did you use "runif(2, min=1, max=6) %>% ceiling", it will never give 2 or 3 as a result because it rounds up. Wouldn't "runif(2, min=0, max=6) %>% ceiling" be better for the double dice roll.

best in class

The illuminati sound 😂🤣 at 5:00

I’m not an expert in R, but wouldn’t you need a uniform distribution from 0-6 if you’re rounding up?

Just a quick note, on 4:27 you said that all random variables have a pdf, but that is not always true. The easiest example is a cdf which is not differentiable, then the pdf can not exist. Much more complicated examples can be constructed, but the previous is a quick one.

"T" is Total?

Man you're the best , keep going bro🤍.

Thanks for the content. Fewer memes please.

Isn't a statistic denoted by "T" because it's also referred to as Test-statistic?

Hello, I admire your enthusiasm and effort trying to make stats more approchable! Thanks :) My 2 cents, I'm half way and learning a few things but how you are saying CDF and PDF too much while running somekind of powerpoint presentation with animations... I just want to say I personally find it distracting. I see you do have github with R code! I would rather have you talk me through this code in jupyter notebooks and spend more time makign those notebooks more accessible and use their ability to plot etc.. You could still thrown in memes and humour and stuff but I would keep the notebook in focus and always refer to it. Maybe it's just me! I don't mean to tell you how to do your thing heh I just find that it is the kind of learning that I need. Cheers!

Not the video if you want to get a refresher on statistics. You're just throwing one definition after another into the explanation. Great... You know your stuff...good on you!

hire a better video editor who can do better do putting the graphics into more intiutiveness ans relatable. your explanation is good but the graphics and animations are not relatable.