Linked Questions

102 votes
31 answers

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

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 ...
BYS2's user avatar
  • 1,475
49 votes
14 answers

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 ...
Elliott's user avatar
  • 543
37 votes
8 answers

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.
user333's user avatar
  • 7,101
20 votes
2 answers

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 ...
mlai's user avatar
  • 493
18 votes
2 answers

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. ...
Patrick's user avatar
  • 832
17 votes
2 answers

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 (...
Sie Tw's user avatar
  • 439
16 votes
5 answers

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 ...
nibot's user avatar
  • 261
14 votes
2 answers

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 ...
BCLC's user avatar
  • 2,394
13 votes
1 answer

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 ...
Uwat's user avatar
  • 567
13 votes
1 answer

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 ...
Yakkanomica's user avatar
11 votes
5 answers

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, ...
Indie's user avatar
  • 113
10 votes
3 answers

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 ...
Bi-Gnomial's user avatar
9 votes
3 answers

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 ...
Chill2Macht's user avatar
  • 6,099
9 votes
1 answer

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 ...
Blade's user avatar
  • 625

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