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

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30 views

Are Latin hypercube samples uncorrelated

I understand the basics to Latin hypercube sampling, such as implemented by the algorithm LHSA mentioned in the book Design and Modeling for Computer Experiments. But I'd like to make sure: 1, n ...
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1answer
19 views

Sampling Distribution question [on hold]

Q: In a certain neighbourhood it is known 12% of school leavers are un-employed if a random sample of 150 school leavers are chosen what is the probability the sample contains: Required: A) At least ...
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25 views

Calculating needed sample size for two stage stratified cluster sample

We want to carry out a survey to assess perceptions of quality and access to medical education of last year students. Based on our research, we have decided that a two stage stratified cluster sample ...
3
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1answer
250 views

Molecules movement distribution puzzle

Let's say I have blood samples of whiteblood cells ($x$) and viruses ($v$). Space has been discretized in $LL$ spaces. They have a $p_v$ probability of interacting when found in the same space. I want ...
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2answers
27 views

Sampling distributions of sample means

Given a population from which we draw repeated samples of fixed size, say, 'n', my questions is what size is considerable? Is there any lower bound on sample size? Also how many such samples do we ...
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23 views

Is it better to use a random sample with 15% response rate or quota sample?

If I use a random sample, it will mean a 15% response rate for around 400 responses. If I use quota sampling using an existing online panel that is representative of the UK population by age, gender ...
3
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1answer
20 views

sample from a von Mises distribution by transforming a RV?

Is there a distribution $p$ that I can sample from, such that for $\epsilon \sim p$, and for closed-form deterministic function $g_{\mu,\kappa}$, $g_{\mu, \kappa}(\epsilon) \sim ...
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13 views

Comparing effect sizes of two treatments from a large number of studies

I suppose this would be some kind of meta-analysis. I would like to compare the effect sizes of two treatments from a large number of published studies. I would like to show that the other treatment ...
2
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2answers
32 views

Distribution of p(x) in empirical model

I am having a hard time to exactly name what I am looking for (I am quite sure it already exists out there...) so I'll start with a concrete example: I have a population of discrete colours (red, ...
2
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1answer
88 views

Sampling from Dirichlet-Multinomial

How do I sample from a Dirichlet-Multinomial distribution. One which has this pmf: http://en.wikipedia.org/wiki/Dirichlet-multinomial_distribution#For_a_multinomial_distribution_over_category_counts
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1answer
34 views

extrapolation and selection bias

I have a cohort of patient data. I have 100 Affected and 900 UnAffected I am reassessing one of the variables for each of the patients, however I can only do so for 90 Affected and 200 UnAffected. ...
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6 views

Sampling comparison groups based proportionality versus real-world frequency

I am looking at differential gene expression (using a t-test) in the context of five Breast Cancer Subtypes. I am working with data in which the distribution of subtypes matches real-world frequency ...
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2answers
41 views

Applying inferential statistics for census data

Let's assume I have a census data of a population which I would like to study and it has variables such as age, gender, sex, occupation etc and the dependent variable which is community participation ...
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1answer
529 views

Which formula is this?

I'm enrolled in a statistics course and missed a few classes so need help in deciphering this formula from a friend's notes. Sorry if this seems a very basic question. I know the formula is somehow ...
2
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1answer
27 views

What role does the sampling fraction play in the simple random sample variance formula?

Consider a survey where the population being estimated is finite. Using a simple random sample, you draw $n<N$ data. The sampling fraction is $f=\frac{n}{N}$. The variance will be ...
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0answers
17 views

Controls sampled on confounding variable

Let's say I wanted to use logistic regression to analyze the effect of an exposure variable on a categorical outcome variable ("yes" or "no"). I believe there are two important confounding variables ...
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1answer
60 views

Gibbs sampling for reducible chain

I am new to Gibbs sampling and I ran into a problem with irreducibility. For the Gibbs sampler to work the Markov chain has to be irreducible. But that assumption is not satisfied in my probability ...
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0answers
24 views

Sampling from Study Population for Labeling

I have the opportunity to get labels for a portion of my study population, and I can determine the subjects that will receive a label. Every subject in the population can be targeted. The labels are ...
0
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1answer
13 views

Estimating population mean when using biased sampling?

Say you had a sample of 50 items that was constructed by taking selecting values that were in the top 75% (not in the first quartile), and you had to take 61 items to find those 50 (11 were in the ...
2
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1answer
72 views

Method for constructing large data set from smaller data set?

Is there a method for creating a large data set from a smaller one? I have a data set of anthropometric variables (e.g. stature, leg length, arm length and so on) So I have 7 variables and 1774 ...
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0answers
8 views

Statistics sampling on over-lapping categories

I got a finite population. (e.g. a pool of files) The objective of the audit is to determine whether the files are in order. I need to audit the files for 5 different category on the population. Each ...
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32 views

Rigorous definitions of sample and population

I am trying to understand some basic ideas of econometrics (and mathematical statistics) from the precise, mathematical point of view, avoiding vague explanations. I am beginning to learn about these ...
2
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0answers
14 views

Normalize(Scale) data before sampling or after sampling in binary classification?

I have a binary classification database with imbalance outputs (1 labeled data: 1400 samples, 0 labeled data: 200 samples). I balance data based on a criteria to (200 - 200). Where should I normalize ...
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1answer
68 views

Why do we need confidence intervals?

I am following a video lecture on Statistics, which introduces the concept of confidence intervals in the following way: "A bank vice president is interested in the average checking account balance ...
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18 views

Time-partitions of sample size

I am struggling with explain something I read in a Whitepaper. The essence is as follows. Let's begin with a random variable $X$ defined as number of events in an hours. Further, we assume that $X ...
3
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0answers
24 views

What would be an efficient way of representing a known discrete distribution with a number of samples?

So, say that I have a known discrete probability distribution, for example: [1] [2] [3] [4] [5] 0.08072 0.0642 0.2853 0.3206 0.2492 What I want to ...
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14 views

Stratified Sampling in 1 dimension

I was planning on implementing a stratified sampling (importance sampling) technique in one dimension. My understanding is that certain procedures need to be followed in determining the partition and ...
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0answers
9 views

Aggregating Equity Intraday Ticks

I am currently working with intraday equity data. The ticks are sourced from Bloomberg API. Bloomberg only timestamps down to the second (not millisecond) and data is not in order. In many instances ...
0
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1answer
69 views

Calculating a p-value from permutations

I have 500 genes I am interested in. I want to test whether they are enriched in a certain dataset (Y). Y is a list of cancer genes that are called cancer genes at different levels of likelihood. I.e. ...
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92 views

Bayesian inference with sampling and mixture models

I'm having some trouble doing Bayesian inference on an experience I have in hands. I apologize in advance if it is too complex, but I couldn't find a trivial way to split it in several parts. Let ...
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48 views

GridWalk sampler with pymc3

I am trying to build a GridWalk sampler (actually PolicyWalk as in BIRL by Ramachandran et. al.. Edit More info: The distribution I am interested in is the reward posterior given by, $$ P(R|D) = ...
3
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1answer
36 views

Weighted sampling as a way to eliminate specific source of variation?

I am facing a problem of predicting probability of an event given two correlated predictors where only one of them is of interest. Thus, I’m trying to eliminate one of them from the model while making ...
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0answers
20 views

Using MARS for imbalanced data

I’m working on my thesis on classification for child labor using decision tree C5.0 algorithm compare with multivariate adaptive regression spline (MARS). I have imbalanced data for child labor (total ...
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4answers
98 views

Standard deviation vs standard error of the mean for intervals

I couldn't find a question like this anywhere on Cross Validated. Also I struggled to write the title for this question. Imagine I have a satellite picture of a straight road, and I expect that the ...
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0answers
8 views

Explanations about the parallel tempering

I am reading this paper on parallel tempering but there are a few things I do not really understand. If I'm not mistaken, parallel tempering is a MCMC method which is quite convenient to sample from ...
0
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1answer
39 views

Adaptive Rejection Sampling in python?

Adaptive Rejection Sampling is a sampling technique for uni-dimensional variables that takes profit of the log-concavity of the probability density. It is used, for instance, in Gibbs sampling, when ...
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0answers
9 views

how to calculate a good quantity of samples for this situation?

I have developed a method for performing steganalysis into pictures. Steganalysis consist in the inverse procedure of Steganography, so what it does is to uncover hidden information into a picture or ...
2
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1answer
25 views

Probability of a deleterious mutation, given an observed distribution of mutations

This problem has been driving me crazy for days, so I finally resort to asking for help here: Consider a set of genes, where each gene consists of a sequence of letters, for example ...
0
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1answer
49 views

Sample size for categorical data

I have a population of phone calls - 200,000. There are different reasons for each call, but lets assume the number of reasons is known. i.e. 7 different call reasons: 1) Check on order 2) Cancel ...
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0answers
25 views

Comparing logistic regression models b/w non-independent samples

I have run a fully adjusted logistic regression model for a sample whose data was collected in the year 2000. The outcome is retirement, and the predictors are individual characteristics, like age, ...
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0answers
15 views

Random Sampling Techniques

I have a pool of people who each have at least one email associated to him/her. Two people can also share a single email. This results in clusters of people chained together by email:person units. ...
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1answer
50 views

Confusion about the sample distribution.. Can you please enlighten me?

I thought that the sample distribution was an approximation of the distribution of the underlying phenomenon. But then the book says: We will denote the sample size by $n$ ($n \le N$) and the ...
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5 views

Prototype selection methods for down sampling

I am looking for some methods for down sampling using prototype selection. I am guessing it is based on nearest neighbors, but I do not know what exact steps they are. Is there any good paper for ...
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0answers
15 views

Sampling of a real time-correlated random variable

I would like to sample numerically the real-value time-continuous random variable $X(t)$, which verifies: $$E[X(t)X(s)]=f(t-s).$$ In my case, $f$ is given by $$f(t)=\frac{1-t^2}{1+t^2}.$$ -My first ...
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6answers
123 views

How to prevent collinearity?

Ieno & Zuur 2015 describe a number of causes of collinearity among explanatory variables entered into a linear regression. One of these causes is what they call a 'data collection' cause. They ...
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0answers
13 views

scoring/predicting for new observations

I have two data sets of variables where one of them - the new observations - has no dependent variable. The data set without a dependent variable has around 20 times the number of records. ...
2
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1answer
63 views

Example of sample $X_1,X_2,\ldots,X_n$

In the book Statistical Inference by George Casella, it is written that An experimenter uses the information in a sample $X_1,X_2,\ldots,X_n$ to make inferences about an unknown parameter $\theta$. ...
2
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0answers
61 views

How many people initially had apples?

Story problem: Assume 10 apples are distributed across $X$ unknown people, where each person has at least one apple. For each apple a biased coin is flipped to see if that apple should be kept or ...
2
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1answer
70 views

How does upsampling rare events affect the interpretation of logistic regression?

The answer to this question can be found here Does down-sampling change logistic regression coefficients? I have a dataset of 50k positives and nearly 1M negatives. Instead of taking a random sample ...
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1answer
45 views

How to make an effective sampling from a database of text documents?

Problem: I want to know methods to perform an effective sampling from a database. The size of the database is about 250K text documents and in this case each text ...