Ironically with loaded dice I would look distribution of results and see that it’s not uniform distribution after a billion tosses and say it’s not fair/ loaded. I would do that simply to avoid figuring out how to prove the probability of a given set of due results.
It’s more about the journey to the p value the calculate p value.
I have seen that 1 drug recovery time example and that’s the easiest given that it’s normal distribution and it can be put into a region that less than 5% probability
Ok but if you’ve done twelve throws, how off does the distribution have to look to cause suspicion? All sixes is obviously off, but what about four sixes? Five? At some point your assessment goes from “probably uniform” to “probably biased”. The p value quantifies that.
I didn’t understand what chat gpt did entirely.
Ironically with loaded dice I would look distribution of results and see that it’s not uniform distribution after a billion tosses and say it’s not fair/ loaded. I would do that simply to avoid figuring out how to prove the probability of a given set of due results.
It’s more about the journey to the p value the calculate p value.
I have seen that 1 drug recovery time example and that’s the easiest given that it’s normal distribution and it can be put into a region that less than 5% probability
Ok but if you’ve done twelve throws, how off does the distribution have to look to cause suspicion? All sixes is obviously off, but what about four sixes? Five? At some point your assessment goes from “probably uniform” to “probably biased”. The p value quantifies that.