Timeline for Baysian Inference with beta-binomial model with different number of trials
Current License: CC BY-SA 4.0
4 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Aug 4, 2023 at 10:31 | comment | added | Tim | @AntonKerel so you want to know what is the probability of seeing 3 successes in 40 trials given that the probability of success is $\mu$ given the posterior beta distribution? This is what I described. | |
| Aug 4, 2023 at 10:17 | comment | added | Anton Kerel |
Thank you, Tim. Sorry for a question that is a bit confusing. You almost understood my question. I can rephrase it a bit. I want to produce a (biased) Bayesian esimator of probability of having 3 successes in 40 tosses given the posterior distribution that I have estimated before. In my mind, Bayesian model always produces a probability of some sort. You can then use the pdf of the posterior to do inference. Therefore, I am interested in the probability of success for 40 choose 3 given that my coin priorly has been estimate to follow $Beta(2,99)$. Does this make sense?
|
|
| Aug 3, 2023 at 15:41 | history | edited | Tim | CC BY-SA 4.0 |
added 284 characters in body
|
| Aug 3, 2023 at 15:34 | history | answered | Tim | CC BY-SA 4.0 |