Linked Questions
34 questions linked to/from Bayesian and frequentist reasoning in plain English
102
votes
31
answers
55k
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Is there a way to remember the definitions of Type I and Type II Errors?
I'm not a statistician by education, I'm a software engineer. Yet statistics comes up a lot. In fact, questions specifically about Type I and Type II error are coming up a lot in the course of my ...
53
votes
9
answers
40k
views
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 ...
- 1,475
49
votes
14
answers
7k
views
Clarification on interpreting confidence intervals?
My current understanding of the notion "confidence interval with confidence level $1 - \alpha$" is that if we tried to calculate the confidence interval many times (each time with a fresh sample), it ...
- 543
37
votes
8
answers
16k
views
What is Bayes' theorem all about?
What are the main ideas, that is, concepts related to Bayes' theorem?
I am not asking for any derivations of complex mathematical notation.
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20
votes
2
answers
5k
views
How to apply Bayes' theorem to the search for a fisherman lost at sea
The article The Odds, Continually Updated mentions the story of a Long Island fisherman who literally owes his life to Bayesian Statistics. Here's the short version:
There are two fishermen on a ...
- 493
18
votes
2
answers
903
views
Frequentism and priors
Robby McKilliam says in a comment to this post:
It should be pointed out that, from the frequentists point of view, there is no reason that you can't incorporate the prior knowledge into the model. ...
- 832
17
votes
2
answers
10k
views
Relation between MAP, EM, and MLE
I am a beginner in machine learning. I can do programming fine but the theory confuses me a lot of the times.
What is the relation between Maximum Likelihood Estimation (MLE), Maximum A posteriori (...
- 439
16
votes
5
answers
1k
views
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 ...
- 261
14
votes
2
answers
24k
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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 ...
- 2,394
13
votes
1
answer
5k
views
Estimating probability of success, given a reference population
Suppose you have the following situation:
You observed over time 1000 bowling players, who each played a relatively small number of games (say 1 to 20). You noted the strike percentage for each of ...
- 567
13
votes
1
answer
1k
views
When can't frequentist sampling distribution be interpreted as Bayesian posterior in regression settings?
My actual questions are in the last two paragraphs, but to motivate them:
If I am attempting to estimate the mean of a random variable that follows a Normal distribution with a known variance, I've ...
- 473
11
votes
5
answers
13k
views
Why would perfectly similar data have 0 mutual information?
I'm not a statistic major, so my knowledge of statistics is quite limited but I've found myself in need of learning about and using mutual information. I believe I understand the concept and formula, ...
- 113
10
votes
3
answers
7k
views
Bayesian AB testing
I am running an AB Test on a page that receives only 5k visits per month. It would take too long to reach traffic levels necessary to measure a +-1% difference between the test and control. I have ...
- 101
9
votes
3
answers
995
views
When (and why) do Bayesians reject valid Bayesian methods? [closed]
From what I have read and from answers to other questions I have asked here, many so-called frequentist methods correspond mathematically (I don't care if they correspond philosophically, I only care ...
- 6,099
9
votes
1
answer
1k
views
Bayesian Bootstrap interpretation
I am using Bayesian Bootstrap for some analysis. Given dataset $X=\{x_1, \dots, x_N\}$, we generate bootstrapped samples $X_1,\dots, X_K$ by sampling from the $X$, with replacement. In classical ...
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