[@YourHeartFeelings]

Thank you very much.a best all in one expalnation

[@zohidbekmahmudjanov7860]

thank you, ive been suffering. u've helped a lot 😇

[@Alchemist10241]

This is when CZcams needs star rating system. I give five star for this video.

[@LynchZT]

literally mate, my lecturer labours through this shit in 4 lectures, going through the proofs of everything, making it seem impossible and make me not want to learn it, you do it in 13 minutes and i understand it perfectly thankyou

[@soumiadje3102]

The true definition of "old but gold". Thank you sir🙌🏼

[@NightbladeNotty]

Thank you for the concise explanations, this is helping shed some light in my class now :D

[@muhammadkumayl7761]

I finally get this!! Went through so many other videos but couldnt get the concept! Nicely done!!!

[@wisdom5603]

This is one of the best explanation on joint PMF....!!! Thank you sir !🙏

[@BoZhaoengineering]

The most advantage I take from your video is you use the most simple example to interpret the idea. Excellent !

[@kangmoabel]

Great lecture !!

[@jinaljain9952]

Thank you so much. It helped me lot

[@senjanusantara]

Thank You!

[@paulbrown5839]

Good video, thanks a lot.

[@alireza98325]

Merci beaucoup Hossein

[@ellenguyen1985]

Thanks for the helpful video! I think there is a mistake at 9:28 though; for Py(y) should it be (xi, y) not (xi, yj)?

[@preetam.ind1]

Thanks a lot !❤

[@SuperAniSmile]

Thank you so much. This is really helpful. :)

[@SadmanPinon]

Good video. I like.

[@disabledassfk]

very well explained

[@KIRAN5P]

So what is the actual answer for the marginal PMFs? Is it 7/24 + 5/12 + 7/24 for pY(y)?

[@serkanerol23]

how can we find E(x) and E(y)?

[@mrxinnovations809]

nice example choice !

[@anweshbhattacharyya7763]

Awesome & 2 some ❤️❤️😀🔥👌

[@yusuffabdulmusawwir6807]

How can I form the table from the diagram

[@anveshvs7671]

At 16th sec, you were telling if...X is discrete...instead of continuous.

[@SequinBrain]

yeah, I had trouble making that out, sounded the same each time.

[@christen-memoseley6833]

I cant understand what you are saying. When you say, "X is a single random variable, For example if x is ..... random variable You usually consider PMF. But if x is a ....... variable you usually consider PDF. Can you tell me the words in between or give me an exact sentence? Thank you P.S. Thanks for the video

[@probabilitycourse3883]

+Christen M Thanks for the comment, what I meant was: If x is a discrete random variable we usually consider PMF. But if x is a continuous random variable we usually consider PDF.

[@dydx3741]

Christen Babe how bout now??? have u understood ??

[@Yuh0847]

@@dydx3741 3 years have gone and no reports if she had indeed understood :(

[@Lisi_Mxo]

Legend has it, till this day she's still trying to understand@@Yuh0847

[@jenniferbundy1424]

Not clear. I cannot understand what you are saying about PMF & PDF at the very beginning of the video. Sounds like you are saying "I call PMF Discrete, but when considering PDF, I call Discrete?????" Please clarify.

[@probabilitycourse3883]

+Jennifer Bundy Thanks for the comment, what I meant was: If x is a discrete random variable we usually consider PMF. But if x is a continuous random variable we usually consider PDF.

[@chitwarnie]

Speak slower that will solve alot of things. I almost refused to continue with this video if you had not explained the "if x is a discrete..." part since i couldnt understand what you were saying

[@amritakaul87]

Jennifer Bundy - pmf is for discrete rv and pdf for continous rv...

[@jacobm7026]

@@chitwarnie CZcams has the option to slow down the video, as well as speed it up. It also allows you to stop watching it if you're going to cry about free information

[@anchitrao7374]

great content, but my ears are shaking

[@forheuristiclifeksh7836]

0:42

[@explore5394]

😭🙏🏻🙏🏻🙏🏻

[@joheunkang7678]

too fast.

[@sabithsabo7986]

Terrible audio

[@zam023]

It is on your end then because I am hearing it just fine.