What is a Cumulative Distribution Function (CDF) of a Random Variable?

[@aezazi]

Thanks so much for this. I have a MS in Engineering, but that was decades ago. At age 60, I decided to essentially go back to school and Learn AI and ML, so having to learn and re-learn this material. This explanation of CDF is extremely illuminating. I now understand the concept better than I did back in graduate school!

[@iain_explains]

Thanks so much for letting me know that you found the video helpful. Comments like these really do help to motivate me to make more videos. I'm so glad to be able to help not just current university students, but anyone interested in these topics.

[@okocha979]

Very simple yet very understandable explanations. Thanks in advance for your future videos.

[@iain_explains]

Glad it was helpful!

[@nagakalyankambapu]

Extremely well explained. Concise and clear

[@iain_explains]

I'm glad you liked it.

[@himanshu1056]

Great one Iain. Thanks for keeping us on momentum.

[@iain_explains]

My pleasure

[@MarcosMynssem]

your videos are awesome. please don't stop doing it

[@iain_explains]

Thanks. Glad you like them!

[@archana9504]

Grateful that i found this playlist 🥳🥳

[@iain_explains]

Glad you like it!

[@空-x2h]

Thank you so much, Professor.

[@iain_explains]

You're welcome.

[@Amine1z]

Please keep making great videos like this

[@iain_explains]

Thanks. That's the plan!

[@algebra7427]

Could we have derived the expression stated at 5:55 by taking the definite integral of the function f(theta). That is, take the definite integral of the uniform distribution (PDF) on the left and integrate between x2 and x1 as our upper and lower bounds respectively? Thanks for the excellent content!

[@iain_explains]

Yes, that's right.

[@rationalthinker9612]

Crystal clear explanation but there's one thing I'm confused on. I'm an EE student taking a Random Signals Analysis class and the textbook section that talks about PDF and CDF states that only discrete random variables have PMF's. In your example, are the functions discrete or continuous? They are drawn like they're continuous so that's my confusion.

[@iain_explains]

I've drawn functions that relate to continuous random variables. Because the RV is continuous, it means the probability function is a "density" function. If the RV was discrete, then the probability function would be a "mass" function. I think I might make a video on this point, because I suspect others may have the same confusion.

[@woltedjidereje8609]

Thank you incredibly much

[@iain_explains]

You're very welcome!

[@bishalpoudel3859]

nice explanation sir

[@iain_explains]

Thanks for liking

[@BB-fp9ce]

I can't understand why the right graph of the cdf is1 after 2pi

[@mohamedlagad]

becouse the cdf range is up to 2pi so after added up must be one

[@Learnwithme.07]

Do you have videos on adaptive filtering? I can't find it on your channel.

[@iain_explains]

Thanks for the suggestion. I've got adaptive filters on my "to do" list. Next week's video is on the Least Squares estimate, so keep an eye out for that.

[@ebrusahin2945]

thanks a lot sir if u solve some kind of problems it would be great , kind regards

[@iain_explains]

Thanks for the suggestion. I'll add it to my "to do" list.

[@JosephAdnan-d7j]

Cdf Zambia

[@JosephAdnan-d7j]

Distribution fonction

[@MelanieMills-c1v]

Perez Ruth Johnson Mark Moore Kevin

[@WalkerVirgil-i6q]

Smith Helen Moore Scott Johnson Sandra