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Statistical test for random sample of data

@Glen_b's answer (and it's comments) is great, but I think I should add the keyword "permutation test" for other readers This seems like a setting for a standard permutation test. Briefly, ...
Alexlok's user avatar
  • 145
1 vote
Accepted

Should I normalise a sample drawn from a skewed population?

If you are interested in the effect of the number of inhabitants, then it makes sense to try and sample a wide range of possible counts. This type of random sampling evenly along some other variable ...
Frans Rodenburg's user avatar
1 vote

Confidence intervals when using stratified proportionate random sampling

With proportionate stratification, if you ignore the strata you will still get an unbiased estimate of $p$, but your confidence interval will (in general) be too wide. For binary data it's not likely ...
Thomas Lumley's user avatar
0 votes

What statistic best estimates the sample mean in case of missing data in a distribution?

Here is an answer assuming that each measured value is reasonably accurate, but that the measurements are incomplete due to overlaps: you might get the median particle length as the $6^{th}$ or $13^{...
Matt F.'s user avatar
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3 votes

How to generate 2 correlated Beta random variables

How can you simulate correlated beta distributed variables? This question has attracted a lot of views, suggesting (future) readers might still be interested in the titular question. I would like to ...
Frans Rodenburg's user avatar
1 vote

What statistic best estimates the sample mean in case of missing data in a distribution?

Here is an answer assuming that the only sample statistics which can be calculated reliably are the size $k_i$ and the maximum $M_i$ of the sample. The question is how to estimate the average $\mu_i$ ...
Matt F.'s user avatar
  • 5,342
4 votes

Why does a 95% Confidence Interval (CI) not imply a 95% chance of containing the mean?

The misinterpretation of confidence intervals is related to what Blitzstein and Hwang (in their probability textbook) call "sympathetic magic". Sympathetic magic is an anthropology term for ...
Abhishek Divekar's user avatar
2 votes

Why do Denoising Diffusion Probabilistic Models (DDPM) add noise according to $\sigma_t$ during sampling?

This is very late, but I had the exact same confusion and managed to resolve it! Your comment earlier about the expression making more sense if it were $\sigma_{t-1}$ is the correct intuition, and is ...
Alex Nguyen-Le's user avatar
1 vote

simple random sampling and in-group comparison

If each visitor purchases only 1 plan, you can make a 4 (plans) by 2 (UI) crosstable, each cell containing the number of purchasers. A common chisquare test could then be used to test if the two UI ...
BenP's user avatar
  • 1,838
4 votes

Quantile regression with sampling weights in R

The weights in rq work like frequency weights, so you get the right point estimates. Using withReplicates will then get you ...
Thomas Lumley's user avatar
3 votes
Accepted

Rejection sampling to obtain a random sample from a truncated version of a multivariate probability density

No, the method described will not result in biased samples for $f_\Omega(\mathbf{y}|\boldsymbol{\theta})$. The reasoning is straightforward: Unbiased Rejection Sampling: The process of rejection ...
Robert Long's user avatar
0 votes

Should pseudoabsences ever be sampled with replacement?

Both resampling and case weights can be used to adjust for sampling bias. Resampling tends to perform better in models that rely on stochastic gradient descent for their optimisation [1]. However, @...
Fiona's user avatar
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