# Tagged Questions

Creating samples from a well-specified population using a probabilistic method and/or producing random numbers from a specified distribution.

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### Is sampling relevant in the time of 'big data'?

Or more so "will it be"? Big Data makes statistics and relevant knowledge all the more important but seems to underplay Sampling Theory. I've seen this hype around 'Big Data' and can't help wonder ...
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### Why at all consider sampling without replacement in a practical application?

Sampling with replacement has two advantages over sampling without replacement as I see it: 1) You don't need to worry about the finite population correction. 2) There is a chance that elements from ...
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### How to resample in R without repeating permutations?

In R, if I set.seed(), and then use the sample function to randomize a list, can I guarantee I won't generate the same permutation? ie... ...
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### Who first developed the idea of “sampling distributions”?

Who created sampling distributions? I have looked everywhere and I'm writing a paper, but, so far, all I've been able to come up with is the theory and the definition. Please help me find the who, ...
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### Suggested books on spatial statistics

What are some of the best books for studying i) variability of univariate and multivariate variables (real, count data) across a spatial domain. ii) sampling a univariate or multivariate variable ...
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### Normal distributed random numbers in time - expected behaviour - askew distributions?

I have a 3D array of numbers, initialised with normal distributed values. The mean of the distribution is $0$, the standard deviation in the order of $10^{-5}$ to $10^{-8}$, but would be constant for ...
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### Given that one can sample $X \sim f(x)$, is there an easy way to sample $Y \sim k \cdot f(g(y))$ (such as $k \cdot f(e^y)$)?

Say I'm able to sample an RV $X$ from a PDF $f(x)$, can I exploit this to efficiently sample another RV $Y \sim k \cdot f(g(y))$ (where $k$ is a normalizing constant)? I'm interested in something ...
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### How do you call this dynamic sample-size selection strategy?

Imagine that you want to assess the compressibility of a large document very fast. You could randomly pick a subsequence, try to compress it. This can serve as a prediction for the overall ...
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### Using MCMC to evaluate the expected value of a high-dimensional function

I am working on a research project that is related to optimization and recently had an idea to use MCMC in this setting. Unfortunately, I am fairly new to MCMC methods so I had several questions. I'll ...
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### How to calculate sample size for comparing the area under the curve of two models?

Because I would like to calculate the sample size for comparing the area under the curve (AUC) of 2 models (cross-sectional study, predictor = continuous variable). Can you point me which function in ...
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### Estimating the variance of poker win rates

Suppose you have a casino with n poker players. Each player has a win rate - the amount of money he wins or loses per hand. We assume that these win rates are normally distributed with a mean of 0. ...
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### Acceptance rates for Metropolis-Hastings with uniform candidate distribution

When running the Metropolis-Hastings algorithm with uniform candidate distributions, what is the rationale of having acceptance rates around 20%? My thinking is: once the true (or close to true) ...
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### Why is random assignment important in stratified sampling?

Background I raised this question because of an argument I am having with a question from user697473 here. The title of his question is "Formal definiton of random assignment." In the post he ...
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### What is the difference between sample variance and sampling variance?

What is the difference between sample variance and sampling variance? They seem same. Aren't they?
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### How can I simulate census microdata for small areas using a 1% microdata sample at a large scale and aggregate statistics at the small area scale?

I would like to perform an individual-level multivariate analysis at small levels of geographic aggregation (Australian census collection districts). Clearly, the census isn't available at these ...
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### Does it make sense to apply a chi-squared test on a contingency table when the whole population has been surveyed?

As I understand it, one of the main goal of the chi-squared test on a contingency table is to determine if the link between lines and columns of the table is "more" than the sampling bias and the ...
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### Recommend references on survey sample weighting

Let's aim for some at an introductory level, some articles and some textbooks. Applied is more helpful, including R code is great. Thanks!
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### With a small sample from a normal distribution, do you simulate using a t distribution?

I want to simulate temperature data for some "what-if" calculations. The problem is, I only have a time series of 10 actual temperature data values. I want to use temperature as an input to the ...
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### How do I sample without replacement using a sampling-with-replacement function?

I vaguely recall from grad school that the following is a valid approach to do a weighted sampling without replacement: Start with an initially empty "sampled set". Draw a (single) weighted sample ...
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### How can I estimate unique occurrence counts from a random sampling of data?

Let's say I have a large set of $S$ values which sometimes repeat. I wish to estimate the total number of unique values in the large set. If I take a random sample of $T$ values, and determine that ...
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### Capture-recapture sampling valid in literary analysis?

So I've been compiling a list of fictional (anime/manga) characters which meet a certain criteria (http://www.gwern.net/hafu#list) from a universe of all anime/manga characters since 1963 (which is of ...
### How to generate a Bernoulli variate with bias $a/\mathbb{E}[X]$ given a sampler of $X$ and uniform variates?
Given: A loaded "die" with unknown probabilities generating a discrete, positive random variable $X$ taking on values in $\mathcal{X}$. A real number $a$, such that $0 \leq a \leq \mathbb{E}[X]$. ...