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

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How are complex sample analysis and GEE different from each other?

I am currently analyzing a national survey data. The survey design is complex: 1) strata 2) cluster 3) 2-stage, 4) sampling weight. There are strata; PSUs(agencies) were selected randomly and ...
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can individuals resampled in reoccurring cross section surveys be considered as panel dataset?

I have data from a reoccurring cross sectional firm survey, For every year a new sample was selected ( with replacement between years). The data is identified, so I can see the subset of firms appear ...
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29 views

How to derive Gibbs sampling?

I'm actually hesitating to ask this, because I'm afraid I will be referred to other questions or Wikipedia on Gibbs sampling, but I don't have the feeling that they describe what's at hand. Given a ...
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384 views

Why does increasing the sample size lower the variance?

Big picture: I'm trying to understand how increasing the sample size increases the power of an experiment. My lecturer's slides explain this with a picture of 2 normal distributions, one for the ...
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21 views

Algorithm for uniform sampling with bounded replacement

Is there a simple algorithm to sample from the uniform distribution on sequences of $n$ numbers, each taking one of $m$ integer values from $0$ to $m-1$, where each value can be repeated at most $r$ ...
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16 views

Inverse sampling for discrete data

I have to pick a ball from a set of balls. Each ball has a size, so I have a distribution for ball sizes (I assume a number between 0-1). I want to pick a new ball each at step with the probability ...
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Derivation of the variance of the sample size in probability sampling

I am trying to understand how to derive the variance of the sample size $n$ in a random probability sample from a population of size $N$ with units $i=1,...,N$. Let $I_i$ be a random variable for $i$ ...
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Inverse CDF sampling for a finite mixture

The out-of-context short version Let $y$ be a random variable with CDF $$ F(\cdot) \equiv \cases{\theta & y = 0 \\ \theta + (1-\theta) \times \text{CDF}_{\text{log-normal}}(\cdot; \mu, \sigma) ...
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Probability of uniformly drawing N numbers less than the expected second highest value

In the case of 3 draws (N=3) from Uniform[0,1], the expected second highest value would be 1/2. Although unlikely it could happen that all three numbers were less than 1/2. It is exactly this ...
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24 views

Do any statistical tests compare distributions when one has significantly fewer samples?

I've been researching different methods to compare two distributions for equality, or inequality rather. I want to compare actual user performance against projected performance, after a particular ...
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1answer
31 views

Quantitative Location Shifting Detection for Run-Sequence Plot

I am trying to complement a Run-Sequence Plot by some quantitative metric to validate that a dataset has a fixed location. Since the Run-Sequence Plot will be used in the early phases of Exploratory ...
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276 views

Best suggested textbooks on Bootstrap resampling?

I just wanted to ask which are in your opinion the best available books on bootstrap out there. By this I don't necessarily only mean the one written by its developers. Could you please indicate ...
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23 views

techniques for sampling graphs? (possibly implemented in r packages)

Let's say I have a very large graph that proves impractical for visualization ends and I wanted to sample a random subgraph. (I know that I can filter out a subgraph via measures like degree, ...
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59 views

Margin of error for mean of group (when mean of each individual can't be calculated)

I am trying to compute the margin of error of a mean of a group. Suppose a have a population of 50 workers and I want to know how much I'm paying as a whole in salary for each sale they perform ...
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Sampling an N-dimensional copula via N independent uniforms

In order to draw a sample from an N-dimensional Gaussian copula, we draw N independent standard Gaussian random variables, form a vector, and multiply it by an appropriate matrix (Cholesky and such). ...
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25 views

Inference possibilities for matched case-control study

We have contracted out collection of survey questions for the group of our customers. These customers even when sampling all of these represent less than 1% our our customer base. We would like to ...
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What factors influence the point at which a sampling distribution is said to be nearly normally distributed?

What factors influence the point at which a sampling distribution is said to be nearly normally distributed? *Note that the answer I am looking for is not sample size. I am asking what decides how ...
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When to Use Sampling Distributions And When to Use Regular Probability Distributions [closed]

Why/When would it be better to use Sampling Distributions such as the Sampling Distribution of the Sample Mean and why/when would it be better to use a Probability Distribution (such as Beta, ...
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70 views

Is oversampling done for Cox regression data?

I have a dataset consisting of about 48000 people, about 40,000 of which die before the end of the study and get a failed = 1 and the remaining 8000 have a failed = 0 because they're either lost to ...
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Unexpected results from Reservoir Sampling Implementation, the probabilities seem to be uneven. Is the implementation correct?

I tried to implement Reservoir Sampling, but the tests indicate that the sampling is not random. ...
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21 views

Gibbs Sampling with given Posterior Distribution

I'm trying to implement an algorithm from a paper which assigns three types of labels $m_i, m_d$ and $m_s$. Here $m_i$ labels a collection of documents $G_i , m_d$ a subcollection of them and $m_s$ ...
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11 views

Gaussian Process Regression with positive prediction weights

I want to do Gaussian Process Regression for a density function $f(x)$ with a gaussian kernel function $k(x, x')$. Given the training data $\mathbf{x} = (x_1, x_2, \dots, x_N)$ and $\mathbf{f} = ...
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PDF of the largest observation in a sample [duplicate]

Intro Let $P(X=x)$ be a Probability Density Function (PDF). Assume we were to perform $n$ observations from a population that is distributed according to $P(X=x)$ (sample size = $n$). I would expect ...
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Does Hoeffding's inequality apply to sampling from finite populations?

Based on Hoeffding's theorem, one could easily find the minimum number of samples required for the inequality $\Pr \left(|\bar{X} - \mathrm{E} [\bar{X}]| \geq t \right) \leq \delta$ to hold as ...
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Sampling from conditional copula under R

this is a follow-up thread dealing with sampling from conditional copulas: Original question (with nice answer by whuber): Sampling from conditional copula Trying to sample from a conditional copula ...
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General questions on MCMC

This is a continuation of the following question. The previous link was related to rejection sampling. This is related to MCMC. General questions on rejection sampling 1a. As far as I understand, ...
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General questions on rejection sampling

I am new to Bayesian methods. I was going through a chapter on sampling. I have a few questions related to it. Please help me get these clarified. As far as I understand, rejection sampling will not ...
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How to determine the sample size, if standard deviation, population mean, sample mean and precision is given?

Determine the sample size if sample standard deviation is 6, population mean : 25, sample mean = 23 and the degree of precision is 99%
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52 views

Why do we estimate population parameters using statistic?

I had been studying statistics, I have a doubt that I couldn't find the answer of. Its related to estimating population parameters using statistic. Suppose we have a population size of 10000, we want ...
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Sampling from a portion of the normal distribution?

I have a a conditional distribution $p(X_1 | \theta) \propto MVN(\mu, \Omega) \pi(X_1)$ where $X_1=[x_1, x_2, \dots, x_n]'$ and $\pi(X_1)=1$ when all $x_i \in [0,a)$ and $0$ otherwise. Is there any ...
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87 views

Justifying the use of finite population correction

Given the fact the finite population correction effectively reduces the standard error of the sampling distribution, which (compared with the lack of a finite population correction) will increase the ...
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Finding n and c in single sampling plan

I am learning a quality control course and in Single sampling scheme for attribute type inspection I don't understand the method used for calculating the values of $n$ and $c$. The method is as ...
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Choosing samples of different sizes - considerations?

Let's say I have four populations with the sizes 2451, 2117, 7577, and 1545. Each of these are sets of activity sequences on which I do sequence analysis. Based on this I want to do clustering based ...
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37 views

Sampling according to a difference of two normal distributions

Assuming that I have two normal distributions $p_1(x)$ and $p_2(x)$ and I can draw samples efficiently from them. Now, I can easily draw samples from $p(x) = 0.5 p_1(x) + 0.5 p_2(x)$ by with ...
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Sampling from conditional copula

I am having trouble finding anything on sampling from conditional copulas. I am only interested in the bivariate case. So, if $C(u,v)$ is my copula, I want to sample from it given a specific ...
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45 views

What sampling method will be suitable when there is no published list is available?

As there is no published list of population (employees), how can I select my sample? Even if I want I can not go for judgmental sampling as the academicians in my University strongly disagree for ...
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47 views

Can I get to an approximation of the population with knowledge of the expansion factor?

Say, I have a set of variables for different villages and for each village I have an expansion factor so I would get a sample representative of each village -- the expansion factor does not change ...
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Correct formula for this example

Population size is $N =10000$. The standard error of proportion estimation must not be larger than $0.02$, i.e., $sh(p)\le 0.02$. In a previous study, the confidence interval of $p$ was between $o.25$ ...
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Upper bound for sampling fraction for CLT to hold

What is the upper bound for the sampling fraction for the Central limit theorem to hold when sampling without replacement? Context The context for my question is that it is regularly argued (see e.g. ...
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Sampling scheme based on newton's method - what is it called?

I recently thought of a crazy sampling scheme, which has almost certainly been thought of by someone else before. I'm interested to find out what it is called, and if it is ever useful. The idea is ...
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Binary Response Models & sample data that contain a disproportionate number of 0's

Sorry in advance if this seems like a dumb question, but I am new to data modeling. I am attempting to classify customer usage as either a case of fraud or legitimate activity. I have attempted to ...
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37 views

nonparametric method to calculate the probability how alike two samples are

I have two samples with each couple of hunderd observations. I want to calculate a probabilty how much they look alike. I'm aware of tests like kolmogorov smirnov but I don't think I need this. I ...
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The population size does not affect the sample size? [duplicate]

I used the following formula to calculate the sample size. n = (Z2 K p (1-p)) / i2; (k = 2, Z = 1.96, p = expected proportion, i = 0.03) I noticed that the sample size is not related to the population ...
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How to select representative sample of companies in a sector and employees within each company?

I'm planning to study how managers use an Information System in a particular sector. There are multiple levels at which I need to do sampling. How many companies and which ones? There are 52 ...
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Prior Probabilities vs Sampling

In case i have a dataset which has 100000 records and only 10000 of them represent Churn cases. Hence before building a predictive model i set a prior probability as 10% for CHURN and 90% for NON ...
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Bivariate sampling for distribution expressed in Sklar's copula theorem?

In the univariate case, one can easily sample a distribution via random numbers $u\sim[0,1]$ and plugging into $F^{-1}(u)$. I have a bivariate distribution constructed via Sklar's theorem on Copulas: ...
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Why is the standard deviation of the sample mean less than the population SD?

The sample means do not vary as much as the individual values in the population. That the sample means are less variable than the individual values in the population follows directly from the fact ...
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Why accept Metropolis-Hastings sample if more probable than previous sample?

One step in the Metropolis-Hastings sampling algorithm is to determine whether a sample $x_i$ is to be accepted based on the previous sample $x_{i-1}$. My understanding is that $x_i$ is accepted with ...
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story about sampling from the phone book?

I was talking with someone today about sampling and vaguely remember a story about some very well-respected statistician recommending systematic sampling from the phone book in a particular legal ...