Bayesian statistics - the basics
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- Опубликовано: 1 окт 2024
- www.tilestats....
1. t-test vs Bayesian two-sample test (00:28)
2. Confidence interval vs credible interval (02:10)
3. Bayes' theorem (04:15)
4. The prior distribution (09:20)
5. How to compute the Posterior distribution with simulations (12:47)
6. How to calculate the credible interval (17:33)
7. Prior * Likelihood (19:37)
8. The highest density interval (HDI) (23:00)
9. How to compute the p-value (24:48)
10. How to compute the Bayes factor (26:21)
Very well explained. Anyone can easily very well understand these concepts. Thanks!!!
This channel and its owner are treasures.
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:
ruclips.net/video/aYqIs4XZli8/видео.html
You are always the master mind, thanks a lot.
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
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:
ruclips.net/video/PRpmA6WsY6g/видео.html
I was always wondering how Bayesian statistics works in an easy explanation. Your video is very helpful! Thank you a lot!
much appreciations for a beautiful rendering of introductory lessons on Bayesian Stats