Thanks for uploading all this content. I am about to begin my masters in data science soon and I was trying to grasp some math theory which is hard for me coming from a CS Background. Your videos make it so simple to digest all these topics.

The clarity you provide--as in, what the zero or 1 on the x-axis of the normal distribution represent but more importantly what they don't represent, which has been a source of confusion (and a drag) for me, is now more clear and finally validates a hunch/H-sub-A I've held; too many terms in statistics which I've encountered have been near-tautologies and a gigantic obstacle for me. In my humble and quasi-researched opinion about learning, cognitive transfer, linguistics, and abstraction, I postulate that for a new subject, especially those often found as hardly intuitive (clearly as a function of many factors), require the most clarity and for me an exhaustive list of features and areas of overlap, as well as an explicit articulation of the areas or features an idea does not connect with. THANK YOU for the excellent presentation!

Great video!

I have questions about statistical inference. Can you help me solve them?

I love how you put the context of sufficiency in real life chance events. Thank you for this gold video!

this is very helpful, thank you so much ❤

After ages of scrolling through the internet to understand what probability means, I finally reach my destination. I always felt that the analogy of 'Probability of flipping a coin' has different interpretations, one being where we can confirm our beliefs after something has happened for a large frequency of time ( Now I can confirm that it is officially called as the FREQUENTIST APPROACH ) and other one where we just know that it is equally likely. Wrapping my head around these concepts and confirming my beliefs was really a painful one. I finally feel satisfied. Thanks Brian for this video.

I freaking love you

AWESOME VIDEO

I'm glad I found your channel. I have never seen a better explanation of mathematical statistics, nobody else is even close! You are doing an amazing job there

you are a genius

This is a great explanation. I love the visuals showing how they are all related. Thank you.

Nice videos. I'm now preparing for my masters and it will be quite useful; the connection between CRLW and the standard error of the estimates by MLE makes this very nice.

Thank you! You made this make total intuitive sense in less than 2 minutes where other videos were taking 10+ minutes and I still didn't have that intuitive understanding

Well done! Thanks for the vid, however the video is a bit too complicated for me.

Great explanation

insane explanation

wow Thankyou Brian, very clear explaination

Please upload more of these videos so helpful

Ain't no one teaches statistics like you ❤ Thankyou soo much for giving such elaborative explanations.. And your illustrations regarding these inequalities made them very simple to understand

Its giving a hint of Heisenberg uncertainty principle

Thx, brother. Making this sht feel like 5th grade math. Ez PZ. wazzup then edit: no diddy, cute eyes brother. go get em

truly fantastic video, watched this and immediately popped off on my homework question. shoutout!

7:26 would have been easier to use the variance formula for uniform: (b-a)^2/12 and rearrange for E(X^2) = var(X)+E(X)

these are perfect! dumbs it down really well while retaining all the info

Thanks!

Thank you!

Thanks for the straightforward explanation!! Now I can understand why "sufficient" is sufficient!

Send love to U! Your Mic is getting better

What if you don't know what's the data distribution?

Finally understood what it means when we say intervals are random in frequentist paradigm.

By God what an absolutely amazing video.

Really impressed with your videos, keep on making more!

I discovered this channel in youtube search and guess what it burnt all my frustration and I love the way to make people understand topic in this video!

Thank you so much! this is so intuitive and funny

It was awesome please continue 🔥

thank you soooooo much. this was so helpful for my college final in mathematical statistics at Texas a&m!!!! you are incredibly gifted!

thank u thank u thank u

thank u so much man u explained it so so well

Thanks

The best explanation on Likelihood ever!!

cheers

Those examples are really good! Gj

thank you so much!

Amazing one! Can we get a video about consistent estimators?

I once flipped a nickel onto the floor, near a wall. It bounced off the floor, one-hopped the wall, and landed on the EDGE of the nickel.

Can you do coupling some time? I know it's important to the earth mover problem.

A Very nice explanation. We poor experimental physicists (and any other scientists whose discipline is base on observations) deal almost exclusively with likelihoods - we use observations to draw conclusions about the (a priori unknown) properties on the actual universe. Theoretical physicists, OTOH, postulate those properties and calculate probabilities of what we _should_ observe. Then we compare the two.

So good! Combined with your video on probability and likelihood, I understand likelihood and MLE so much better now.

I’ve had 7 statistics courses at the graduate level, and no one has ever explained what likelihood is. Thank you.