Understanding Probability Density Function (PDF) | Explained By Michael

In which we dive into the meaning behind Probability Functions (PMF, PDF) and understand how to a) derive meaning from the graph, b) draw one of our own, and c) formulate an expression to describe the graph.

This video is the first in a series on probability and statistics. I am dedicated to explaining topics conceptually rather than formulaically. If there is a topic you are having a hard time grasping, please leave a comment letting me know! I want to help maths and engineering students reach true comprehension, not just plugging in numbers.

[fjsp]

Michael, your explanation is very clear, I appreciate it very much. Helped me to understand the concept

[shashankbakshi]

You are a god I learned this in just 10 minutes which my teacher couldn't do for almost 3 months...

[DhrubSatyam]

Most underrated explanation on youtube. Great work buddy, way to go !! Love from India!

[sassonebrott]

Hey mate, just wanted to let you know this is a clear and concise explanation and really helped me fully understand the concept. Thank you

[manishbasotia]

Very well explained, some time we miss these kind of explanation online

[jdmc]

THANK YOU- greatly appreciated. No waffle- straight to the point

[vivekramayanam]

I really appreciate your efforts on this video. But the example you have taken is a dicrete random variable which is here rolling dice example and it accounts to Probability Mass function but not PDF. PDF is specifically for the measurements or precisely taken for Continuous random variables. Eg: Measuring height of students in a class and Y - Axis on PDF gives the % of distribution.
It will be really nice if you explain all these differences in an another video.

A big cheers for your hard work on all these

[ediblepeachey]

Appreciated the sped up writing part and no having on of those annoying intros and getting straight to it. Thanks!

[destinystanley]

Thank you so much. I appreciate you making it crystal clear. I watched many videos but this definitely made it all make sense. Keep making videos!!!

[nsenthil]

Enjoyed watching this. The slow pace of talking helps in understanding and absorbing the content. I hope all math can be taught this way.

[fliederblumen]

Miachel, thx for the video, but y axis is not always standing for probability, especially in the case of bell curve of normal distribtion, the area under the curve stands for probability

[mlsivaprasad]

Thank you so much Michael. You are a fantastic teacher. Looking forward to see more videos and Kudos!

[sakshikaluskar]

You teach concepts to the point. Can you please upload a video on Probability generating Function and Moment generating function. I am not able to find any good video on PGF and MGF.

[bhaskarroy]

Excellent explanation Michael. Thanks a lot. Do you plan to do any video on the inverse transform theorem?

[RyanLBuchanan]

Briliant! Thanks so much for taking it slow & even!

[randomviews]

thank you very much for this video. You are a great teacher and i wish you the best of luck.

[solbanan]

Thank you! (Side note: the blinking signs were a bit distracting)

[JustinGarfield]

You have a video on quantum numbers? I have the book and I watch videos but it feels like there are missing pieces of information that can help me connect what I have learned.

Thanks.

[farheenahmed]

Please make vedios on joint pmf, pdf and cdf

[abhishekaswal]

Can u explain kappa-mu fading distribution in your video or any other reliable source you can mention