Questions tagged [frequentist]

In the frequentist approach to inference, statistical procedures are assessed by their performance over a hypothetical long run of repetitions of a process deemed to have generated the data.

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6answers
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How seriously should I think about the different philosophies of statistics?

I've just finished a module where we covered the different approaches to statistical problems – mainly Bayesian vs frequentist. The lecturer also announced that she is a frequentist. We covered some ...
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3answers
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How to answer critiques about the inapplicability of the framework of frequentist statistics to the real world?

I often hear the argument that frequentist stats is useless or contorted because no event is precisely repeatable, let alone repeatable infinitely many times, and because there are no iid sequences in ...
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Should Likelihood add to 1 in frequentist case? [duplicate]

I know maximum likelihood and Bayes formula works for both frequentist and Bayesian approach. We know there are two approaches to statistics, and likelihood is a term that is used in both frequentest ...
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1answer
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Why isn't the probability of an event happening in $L$ days given the probability $p$ it happens on any day $\frac{(2^L - 1)}{p^{-L}}$?

I feel like this is probably a dumb question, but there is something I am fundamentally misunderstanding here. The problem is essentially the same as the one mentioned in this question. I understand ...
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0answers
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Upper Limits in High-Energy Physics

I am not sure where to write my question. This is a Particle Physics question, but it has more to do with Statistics than with Physics, I think. Please tell me if this is not the right site. So: In ...
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1answer
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Why do we assign probability to theta even though we consider it constant in frequentist statistics? [duplicate]

i am trying to understand the differences between bayesian and frequentist statistics. I read that in frequentist statistics the unknown population parameter theta is considered a constant but in ...
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0answers
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Population distributions/data generating functions in Bayesian Statistics

In many frequentist stats courses, random variables come from some distribution at the population level and as such we could say that $y=X \beta + \epsilon$ is the true function for something like ...
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0answers
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Regression methods for indicator function as covariate

I am looking for a regression method to fit the following model: $$Y=\beta_0 + \beta_1X+\beta_2 I(X>\beta_3)X + \varepsilon,$$ where $\varepsilon \sim N(0, \sigma^2)$, and $I$ is the indicator ...
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Adjusting probabilities when testing lots of subgroups

If you fit the same regression lots of times to noise, you get a coefficient significant at 5%, 5% of the time. If you have lots of subgroups, and you fit the same regression to each of the subgroups,...
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1answer
31 views

Interpretation of GAMM with Factor level Predictors

I'm running the following model in R using the package mgcv: ...
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1answer
27 views

Frequentist Regression Analysis & Pearson's $r$

I find that a polynomial trend line gives a better $r^2$ value. Is Pearson's Correlation Coefficient $r$ still a good indicator in this scenarios between the strength of correlation between my two ...
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1answer
134 views

frequentist vs Bayesian approaches to Gaussian Processes?

I've been reading this blog post, which has been tremendously helpful in understanding Gaussian Processes (GP.) The author has used the terms "prior", "posterior", and "95% ...
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Need Concrete Example of Where a Frequentist Clustering Technique Outperforms the Existing Bayesian Clustering Techniques

I'm looking for a concrete example of frequentist clustering outperforming Bayesian clustering (using the best Bayesian algorithm for the problem, using the testing criteria below). There are many ...
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4answers
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What about the “p-value” of the non-null hypothesis?

So my understanding is that the p-value is the likelihood of observing an effect at least as extreme as that shown in the sample data, if the null hypothesis is true. But how is this a useful value? ...
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0answers
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Does the Bernstein–von Mises theorem imply convergence in distribution between a Bayesian estimator and the MLE analogue?

Does the Bernstein–von Mises theorem imply convergence in distribution between a Bayesian estimator and its MLE analogue? Say I have \begin{equation*} \begin{aligned} & \mu \sim N(m, s^2) \\ & ...
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0answers
30 views

Probabilistic predictions from a frequentist point of view [duplicate]

I'm trying to understand how a frequentist would approach statements like "having observed X, the probability of Y happening is Z". For concreteness, let's say we conducted $n_1$ identical, ...
3
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1answer
44 views

How to calculate the winning probability for Tottenham vs LiverPool? [closed]

I wonder how frequentist and bayesian calculate the winning probability for Tottenham versus Arsnel, Saturday. For frequentists, the following is how I understand: Imagine a population made of all ...
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0answers
26 views

How would Bayesian Statistics overcome a problem that Frequents would encounter?

For example, I want to calculate the probability that measures the winning chance of England against Italy in the World Cup. For this problem, I wonder how frequentists with what specific assumptions ...
0
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1answer
38 views

Is there an R package that runs frequentist zero-one inflated beta models? [closed]

I have a set of proportion data (below) with a many 1s. I would like to run a one inflated beta model in R, and want to use frequentest statistics. However the only zero-one inflated beta package I ...
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1answer
31 views

True parameter in relation to credible interval

I know that in the frequentist approach, the confidence interval contains the true parameter $\theta$ with some minimum probability (e.g. 95%); while in the bayesian approach, the credible interval ...
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1answer
44 views

How to find variance within and between batches

I have some data for 5 different batches of bacteria counts with 5 observations each - Batch 1: 3.890, 4.675, 7.345, 2.950, 5.675 Batch 2: 4.345, 5.875, 3.665, 2.935, 5.455 Batch 3: 7.145, 5.550, 6....
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2answers
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Lost in multiple comparisons: is there a princepled way out?

Suppose I am planning to run some well-powered factorial experiment based on a random sample with several treatments and several levels. I am interested in the effects of all of all levels vs. some ...
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0answers
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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 ...
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1answer
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How can I use Bayesian statistics to test this particular hypothesis?

There is a set $R=\{r_1, r_2, ..., r_K\}$ of $N$ ranks (where $N>> K$). I test the hypothesis that the ranks in $R$ are not homogeneously distributed in $\{1, 2, ..., N\}$. As I am interested in ...
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1answer
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Bayesian vs. Frequentist results question [closed]

A researcher computes both a frequentist confidence interval, and a Bayesian credible interval. After the computation, the researcher realizes that the credible interval is much more narrow than the ...
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2answers
174 views

Frequentist vs Bayesian and deterministic vs stochastic [closed]

So this is sort of a general/basic, likely dumb question. I'm hoping to get a general idea, to better guide what I search/read. How do these terms relate to each other. I know with Bayesian theory, ...
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What does “Parameters are fixed and data vary” in frequentists' term and “Parameters vary and data are fixed” in Bayesians' term exactly mean?

I hear the sentence in my question a lot, I kind of understand what it means but never have a clear picture of it. Hope to get the clear picture of what the sentence exactly mean.
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Reporting: using bayesian and frequentist statistics interchangeably in a study

What would you expect to read in a work's "data analysis" or "statistics" section if this used Bayesian and frequentist methods interchangeably? I used Bayesian regression, since ...
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1answer
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Is Bayesian estimation useful for causal analyses?

Is Bayesian estimation useful for causal analyses? For analyses like randomized experiments or even observational studies of natural experiments, we want unbiased estimators of the causal effect (...
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2answers
232 views

Is Frequentist Inference Objective?

Bayesian statistics is criticized for being subjective, as it requires a prior distribution encapsulating the subjective befiefs of the observer. Frequentist statistics is commonly advertised as being ...
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1answer
43 views

Crossing Frequentism and Bayesian Analysis

Has anyone considered giving the posteriors of an analysis a sampling distribution and seeing where, methodologically, things could go from there? For details, check out: https://sdba-stats.weebly.com
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Generate binary classification data in python?

Is there a simple way to generate binary classification data in python? I'd like to specify $X$ input parameter, $[x_1,...,x_n]$, and generate a dataset such that the (overall) McFadden's pseudo $R^2$ ...
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5answers
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“It was the correct play even though I lost”

*sorry if this isn't the right SE community, maybe it's more philosophical* You often hear this refrain in games like Poker or Hearthstone. The idea is that making play A this game resulted in a loss, ...
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1answer
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Coin flipping: Relationship between Bayesian and Frequentist's point estimates

I have a (biased) coin that has an unknown Head probability $p\in(0,1)$. To point estimate $p$, say that I'm going to use two approaches. Approach 1. I can use the Bayesian inference technique. ...
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Statistical Significance: Can we apply the concept of Statistical Significance when reading the results of AI driven marketing?

Really need to know this from someone who really understands statistical significance. Can we apply Statistical Significance when reading the results of AI driven marketing? Challenge: Large ...
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1answer
341 views

Can Random Forest be considered as a Frequentist method?

I am very new to machine learning so I apologize if this is a silly or even a repetitive question. I am running a Random forest model in R and was just wondering whether this is a frequentist method ...
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Is the admissible minimax decision rule ever a randomized action in frequentist statistics?

Are randomized action as opposed to pure action ever an admissible minimax rule in frequentist statistics,
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1answer
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Bayesian vs Frequentist Prediction Methods and Frequencey Garantees

After reading Larry Wassermans blog on the difference between Bayesian and Frequentist inference I started to appreciate that frequency guarantees can be desirable regardless of the inference method ...
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0answers
48 views

Frequentist approach to marginalize nuisance parameters

How would be a frequentistic approach to solve this problem? "We have a random machine that gives 0 or 1 with a hard-coded, fixed but unknown probability $p$. After 10 trials we have 5 "0&...
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0answers
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Interpretation of sampling distribution as the main distinction between Bayesian and classical statistics (Leamer)

In Hendry et al. (1990) p. 187-188, Edward Leamer says: To me the essential difference between the Bayesian and a classical point of view is not that the parameters are treated as random variables, ...
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1answer
419 views

brms intercept only model runs very slow

I am trying to learn brms package for multilevel modeling. A reproducible code is as below: ...
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3answers
63 views

Is there a name for, or interpretation of, very high p values?

If I flip a coin 1000 times and get only one head, I may suspect that the coin is biased. One justification for this suspicion is that I am unlikely to get so few heads under the null hypothesis of ...
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0answers
26 views

Parameters Quantification in Bayesian and Frequentist Approach

I am looking at a lecture on Bayesian Statistics and Why Bayes it is mentioned that, say the data can be modelled with normal distribution, the frequentist approach is to keep the $\mu$ and $\sigma$ ...
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1answer
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De Finetti's Coherence Principle and Frequentist interpretation

So, without proof or citation, I often see that the Coherence Principle by de Finetti does not hold with Frequentist statistics. It is pretty easy to create examples of this fact. The exception ...
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2answers
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Does there exist a Frequentist or Non-Bayesian solution to Gull's Lighthouse Problem?

Does there exist a Frequentist or ODE or Non-Bayesian solution to Gull's Lighthouse Problem which is correctly modeled with cauchy distribution? See The Lighthouse Problem and Dave Harris' answer to ...
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3answers
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Would you say this is a trade off between frequentist and Bayesian stats?

I'm trying to review frequentist and Bayesian in parallel. Let's say we are doing the typical scenario of estimating the population mean. In frequentist stats, if sample size is large enough, we ...
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4answers
655 views

Does Bayesian statistics bypass the need for the sampling distribution?

Let's take the classic case where the population follows a normal distribution, observations are iid, and we want to estimate the mean of the population. In Frequentist stats, we calculate the ...
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2answers
284 views

What is the Frequentist definition of fixed effects?

Bolker (2015) writes on p. 313 that Frequentists and Bayesians define random effects somewhat differently, which affects the way they use them. Frequentists define random effects as categorical ...
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What is two tailed test actually testing?

I know the two-tailed test procedure, that's not the issue. I am wondering about the philosophy about it. The null hypothesis $ \mu = X $ makes sense to me, we assume a certain value for the ...
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2answers
39 views

How to interpet this equation? [closed]

Can I get some help on interpreting this equation? Is it saying which ever section separated by the commma is bigger would be the answer? How do you intepret Sigma pi= 1? Thanks!

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