Thank you for the video! I remember reading a short paper a few years back that the regular P value is equivalent to the probability that H1 is more likely than H0 with an unspecified (uniform?) prior. Please correct me if I am mis-stating this... Long story short, I can't find that paper anymore. Could you or anyone else please help me find that paper again? Thank you!
It is the likelihood. When you are trying to estimate the parameter p based on observed data (6 successes out of 8 trials), you are using it as a likelihood function. You may watch this video to get a better understanding: ua-cam.com/video/PRpmA6WsY6g/v-deo.html
This channel and its owner are treasures.
I was always wondering how Bayesian statistics works in an easy explanation. Your video is very helpful! Thank you a lot!
You are always the master mind, thanks a lot.
Amazing Explanation
Very well explained. Anyone can easily very well understand these concepts. Thanks!!!
much appreciations for a beautiful rendering of introductory lessons on Bayesian Stats
Could you please provide the detailed code for this example to help me understand the visualization more clearly?"
Dear Sir,
could you tell me a reference book that could help me for more information.
I am grateful for this wonderful video you made.
Thank you sir
Thank you for the video! I remember reading a short paper a few years back that the regular P value is equivalent to the probability that H1 is more likely than H0 with an unspecified (uniform?) prior. Please correct me if I am mis-stating this... Long story short, I can't find that paper anymore. Could you or anyone else please help me find that paper again? Thank you!
Sorry, I meant to say that H0 is more likely than H1, of course.
I have not seen that paper, but if you like to learn more about p-values, I have a video on that:
ua-cam.com/video/aYqIs4XZli8/v-deo.html
Here , 'Binom(6,8,p)' is this a likelihood or conditional distribution of x given parameter? [ f(x | p) ]
I think both are same 🙂 or I don't know.
It is the likelihood. When you are trying to estimate the parameter p based on observed data (6 successes out of 8 trials), you are using it as a likelihood function. You may watch this video to get a better understanding:
ua-cam.com/video/PRpmA6WsY6g/v-deo.html