Linked Questions

4 votes
2 answers

Can someone explain why Bayesian networks are called "Bayesian"

I have been reading Jensen's book on Bayesian Networks and Decision Graphs as well as the Deep Learning book by Bengio, et. al. I am trying to understand why undirected graphs are referred to as ...
krishnab's user avatar
  • 1,502
3 votes
2 answers

Question about the true nature of errors

In frequentist statistics, in regression analysis, errors, like random variables, have a distribution. Errors, like parameters, can be estimated and the residuals of the model are their estimates. So ...
John M's user avatar
  • 2,097
1 vote
2 answers

Bayesian : Comparing means of two posterior samples/ Help a Frequentist Out

UPDATE Thanks for the many thoughtful responses and questions! I've made edits here to clarify further. and also respond to each respondent individually. Original Post I have two sets of posterior ...
pythOnometrist's user avatar
1 vote
2 answers

(Failure) probability calculation

I am working on mortality in 12 hospitals performing cardiac surgery in babies. The dataset is available here: Surg dataset. The dataset is structured in this way: ...
Fabio's user avatar
  • 153
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
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
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
1 vote
1 answer

Include prior knowledge in regression model

I've a classical dataset with real attributes and I want to perform a regression. But, not all the entries in the training dataset are trustworthy; there is an attribute that I can turn into a ...
Ghilas BELHADJ's user avatar
0 votes
1 answer

Repeated Measures ANOVA post hoc test (bayesian)

I am trying to understand the procedure of carrying out a Bayesian Repeated Measures ANOVA. In a conventional repeated measures ANOVA, I calculate the effect of a certain parameter (e.g., study ...
WalterB's user avatar
  • 53
0 votes
1 answer

Bayesian vs. frequentist view [duplicate]

I have tried to figure out the difference between the two views of looking at the world: Bayesian and frequentist. Can someone please let me know if I have it right? (Please do not refer me to some ...
kte80's user avatar
  • 42
0 votes
1 answer

What to do with important features?

I am currently solving the titanic problem in kaggle. The data of the problem consists of several features such as "sex", "class in society", etc., and you are to predict whether a person survived the ...
hehe's user avatar
  • 211
7 votes
0 answers

Probabilistic (Bayesian) vs Optimisation (Frequentist) methods in Machine Learning [duplicate]

Possible Duplicate: Bayesian and frequentist reasoning in plain English A very similar question was posed on stats.SE: Bayesian and frequentist reasoning in plain English, which provoked some ...
tdc's user avatar
  • 7,559
2 votes
0 answers

What is Bayesian and Monte Carlo Simulation? [duplicate]

Can someone explain in plain language for a layperson what are Bayesian and Monte Carlo simulations and the relationship between the two? I thought Bayesian was the same as Monte Carlo Simulation...
Sally7874's user avatar
1 vote
0 answers

Does bayesians' critique to frequentists apply to themselves too?

I've been reading about bayesians versus frequentists, including articles in this forum (like this one). Key is of course the issue of "priors". The bayesian critique being that frequentists ...
chatGPT's user avatar
  • 127
1 vote
0 answers

The difference between the Frequentist, Bayesian and Fisherian appraoches to statistical inference [duplicate]

I'm just trying to get my head around the differences between these three approaches to statistical inference. I'm just not entirely sure what the significant differences are between the three.
user143951's user avatar

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