Yeah I think so. I think it's a way of highlighting that principles of parsimony play a fundamental role in determining scientific hypothesis - it's a...
I'd been thinking along similar lines. To learn something isn't to learn something in a vacuum, it's to learn within a context. So in terms of the pic...
Another contrast I thought of is that in Bayesian methods, the data are considered as fixed quantities in the likelihood and hypothesis tests are done...
You can look at the probability of a random variable belonging to a set, you can't look at the probability of a fixed quantity belonging to a set (it'...
It's a line at y=1 between x=0 and x=1, exactly. You can consider the infinite binary sequences (with trailing zeros) as numbers in . Also, for the un...
The procedure for going from a null hypothesis and an alternative hypothesis to a p-value with its usual interpretation is what being a strict Bayesia...
I feel the same about algorithmic information theory, had to Wiki to make sure the vague recollections I had of incompressibility and complexity weren...
I had in mind processes which are modelled using random variables rather than the conception used in algorithmic information theory. Most real numbers...
Randomness isn't an absence of any pattern. Most things which can be considered as random have patterns. The basic example is a fair coin, flipping it...
@"sime" Change the thought experiment so that a person who's never seen it before and isn't compelled by the assumptions to see only a duck or only a ...
I'm not sure what you mean, regardless have some words. Let's refine it a little bit. Steve and Sally are asked to determine whether the image is of a...
Since you offered a summary post I'll give one too. Saying 'it's BS' wouldn't've let me wrestle with some relevant ideas I recently encountered (causa...
Whenever someone looks at an ambiguous figure, like the duck-rabbit, their perceptions are in such a state of undecidability: 1) Person sees a duck. 2...
@"SophistiCat" I think so. But I don't think this accounts for whether Bayesian approaches to AI and the mind are correct or not. In my view AI questi...
I don't think we can check if she literally saw the implement, descriptions of experience are all we have to go on. There are plenty of other things s...
A summary of the argument: if the sampling behaviour of supposedly veridical NDE experiences matches the sampling behaviour without reference to NDE, ...
In summary: I think the veridicality of NDEs turns on their aggregate properties, rather than the accounts of NDEs made by specific individuals. I don...
I agree that a raw proportion of people not having NDEs isn't good evidence that NDEs content is non-veridical. I'm glad of your example because it pi...
There's usually a Bayesian or frequentist method to do anything. The major reasons people choose to use Bayes or frequentist afaik is pragmatic, more ...
@"Sam26" I'm interpreting the OP an the other posts you have made as invitations to analyse whether the testimony of people who have NDEs is sufficien...
The thrust of the comments is that contemporary statistics uses plenty of methods and mathematical objects that are not consistent with contemporary p...
Human thought is consistent? Human mathematical thought isn't consistent. Within a specific formal system, sure, but there are intuitionist, construct...
@"Sophisticat" There's a big probability I'm being unfair based on unfamiliarity with the literature, just whenever I've read philosophy of statistics...
I read a few things on likelihoodism and other ideas of what is the 'right way' to show that data favours a hypothesis against a (set of) competing hy...
@'StreetlightX' I read this and the developments in the thread a few times, there's something I'd quite like to highlight with regard to the generalis...
@'SophistiCat' I've not met likelihoodism before, do you have any good references for me to read? Will respond more fully once I've got some more fami...
It's probably true that for every Bayesian method of analysis there's a similar non-Bayesian one which deals with the same problem, or estimates the s...
I'm not slick at all. The game I'm playing is 'What can I do to understand whatever disagreement I have with Jeremiah?', now that 'Asking Jeramiah to ...
You claimed that I was misunderstanding your points and that all my comments are off the mark. I gave you an opportunity to set me straight. No, null ...
I'm really not. What actually is your question, and what do you think we disagree on? What is the distinction between choosing and making that you ref...
With regard to regularization and shrinkage, these are reasons to choose a distribution not because of the way it represents the probability of events...
The long post I made details a philosophical distinction, between frequentist and Bayesian interpretations of probability. I presented the distinction...
There are lots of motivations for choosing prior distributions. Broadly speaking they can be chosen in two ways: through expert information and previo...
If copy-pasting the response in the other thread to you is what it takes to get you to stop being petulant, here it is: This is a response to @Jeremia...
Markov Chain Monte Carlo uses a Bayesian interpretation of probability. The methods vary, but they all compute Bayesian quantities (such as 'full cond...
If you're a strict Bayesian the vast majority of applied research is bogus (since it uses hypothesis tests). If you're a strict frequentist you don't ...
One last thing I forgot: you can see that there was no mention of the measure theoretic definition of probability in the above posts. This is because ...
Honestly, direct mockery and non-collaboration from the frequentist paradigm of statistics was something that troubled the field up until (and after) ...
Summary: Frequentist - fixed population parameters, hypothesis tests, asymptotic arguments. Bayesian - random population parameters, likelihood ratio ...
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