Linked Questions
38 questions linked to/from How exactly do Bayesians define (or interpret?) probability?
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How are bayesian probabilities represented in a probability space? [duplicate]
Given that bayesian probabilites are updated over time, how is this represented in a probability space? More specifically, how do we interpret the probability measure of such a space? That is, ...
user134076
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Bayesian vs frequentist Interpretations of Probability
Can someone give a good rundown of the differences between the Bayesian and the frequentist approach to probability?
From what I understand:
The frequentists view is that the data is a repeatable ...
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Examples of Bayesian and frequentist approach giving different answers
Note: I am aware of philosophical differences between Bayesian and frequentist statistics.
For example "what is the probability that the coin on the table is heads" doesn't make sense in ...
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Is everyday probability just a way of dealing with the unknown (not talking quantum physics here)?
It seems like in everyday probability (not quantum physics), probabilities are really just a substitute for an unknown. Take a coin flip for example. We say it's "random," a 50% change of head and a ...
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Conditional probabilities - are they unique to Bayesianism?
I wonder whether conditional probabilities are unique to Bayesianism, or whether they are more of a general concept that is shared among several schools of thought among statistcs/probability people.
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How do Bayesians interpret $P(X=x|\theta=c)$, and does this pose a challenge when interpreting the posterior?
I have seen the post Bayesian vs frequentist interpretations of probability and others like it but this does not address the question I am posing. These other posts provide interpretations related to ...
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Is there more to probability than Bayesianism?
As a student in physics, I have experienced the "Why I am a Bayesian" lecture perhaps half a dozen times. It is always the same -- the presenter smugly explains how the Bayesian interpretation is ...
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Do Bayesians accept Kolmogorov's axioms?
Usually probability theory is taught with Kolgomorov's axioms. Do Bayesians also accept Kolmogorov's axioms?
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Bayesian logit model - intuitive explanation?
I must confess that I previously haven't heard of that term in any of my classes, undergrad or grad.
What does it mean for a logistic regression to be Bayesian? I'm looking for an explanation with a ...
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Using p-value to compute the probability of hypothesis being true; what else is needed?
Question:
One common misunderstanding of p-values is that they represent the probability of the null hypothesis being true. I know that's not correct and I know that p-values only represent the ...
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Within the frequentist "school of thought" how are beliefs updated?
Background
Edit: I realize my use of the word "hypothesis" is confusing, I do not mean specifically a null hypothesis. I mean a proposition that something is true.
From my limited ...
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Is the "Bayesian approach" about prior beliefs, viewing parameters as random variables, or both?
It seems to me like the concepts of incorporating prior beliefs about parameters VERSUS viewing parameters as latent random variables are two VERY separate concepts, and yet I've found that they're ...
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Is OLS the frequentist approach to linear regression?
In this Wikipedia article, there is this sentence:
This is a frequentist approach
Is 'this' referring to OLS?
Is it really 'a' rather than 'the'? What are some other frequentist approaches? As ...
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What exactly does it mean to and why must one update prior?
I'm still trying to understand prior and posterior distributions in Bayesian inference.
In this question, one flips a coin. Priors:
unfair is 0.1, and being fair is 0.9
Coin is flipped 10x and is ...
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Mutual Information as probability
Could the mutual information over the joint entropy:
$$
0 \leq \frac{I(X,Y)}{H(X,Y)} \leq 1$$
be defined as:"The probability of conveying a piece of information from X to Y"?
I am sorry for being ...
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