in the theory relating to sampling from finite populations, the sampling probability (also known as inclusion probability) of an element or member of...
2 KB (281 words) - 15:41, 9 June 2024
survey sampling, weights can be applied to the data to adjust for the sample design, particularly in stratified sampling. Results from probability theory...
54 KB (7,394 words) - 02:23, 17 July 2024
Nonprobability sampling is a form of sampling that does not utilise random sampling techniques where the probability of getting any particular sample may be calculated...
7 KB (799 words) - 09:12, 20 May 2024
conducting a probability sample of the household population in the United States are Area Probability Sampling, Random Digit Dial telephone sampling, and more...
14 KB (1,725 words) - 16:04, 29 March 2024
In statistics, a sampling distribution or finite-sample distribution is the probability distribution of a given random-sample-based statistic. If an arbitrarily...
7 KB (729 words) - 14:36, 17 May 2024
In survey methodology, probability-proportional-to-size (pps) sampling is a sampling process where each element of the population (of size N) has some...
3 KB (347 words) - 13:27, 28 September 2023
description of a random phenomenon in terms of its sample space and the probabilities of events (subsets of the sample space). For instance, if X is used to denote...
47 KB (6,403 words) - 09:00, 5 August 2024
the sampling probability is known, from which the sampling population is drawn from the target population, then the inverse of this probability is used...
14 KB (2,595 words) - 06:53, 15 May 2024
phenomenon under study rather than to the method of sampling. Medical sources sometimes refer to sampling bias as ascertainment bias. Ascertainment bias has...
23 KB (2,877 words) - 16:31, 3 May 2024
statistics, Gibbs sampling or a Gibbs sampler is a Markov chain Monte Carlo (MCMC) algorithm for sampling from a specified multivariate probability distribution...
37 KB (6,144 words) - 02:30, 20 June 2024
small sample from a large population, sampling without replacement is approximately the same as sampling with replacement, since the probability of choosing...
12 KB (1,789 words) - 17:28, 5 April 2024
obtaining a sequence of random samples from a probability distribution from which direct sampling is difficult. New samples are added to the sequence in...
30 KB (4,535 words) - 20:02, 13 June 2024
Inverse transform sampling (also known as inversion sampling, the inverse probability integral transform, the inverse transformation method, or the Smirnov...
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general purpose unequal probability sampling plan". Biometrika. 69 (3): 653–656. doi:10.1093/biomet/69.3.653. Tillé, Yves (2006). Sampling Algorithms. Springer...
21 KB (3,520 words) - 14:05, 30 July 2024
Design effect (redirect from Effective sample size)
cluster sampling we can use a two stage sampling in which we sample each cluster (which may be of different sizes) with equal probability, and then sample from...
97 KB (13,064 words) - 10:36, 30 June 2024
value of the random variable would be equal to that sample. Probability density is the probability per unit length, in other words, while the absolute...
30 KB (4,938 words) - 16:36, 31 May 2024
Probability theory or probability calculus is the branch of mathematics concerned with probability. Although there are several different probability interpretations...
26 KB (3,611 words) - 14:58, 26 March 2024
p_{i}} ). If all first-order inclusion probabilities are equal, Poisson sampling becomes equivalent to Bernoulli sampling, which can therefore be considered...
2 KB (285 words) - 13:21, 28 September 2023
In probability theory, the sample space (also called sample description space, possibility space, or outcome space) of an experiment or random trial is...
15 KB (1,893 words) - 01:50, 18 January 2024
sampling formula describes the probabilities associated with counts of how many different alleles are observed a given number of times in the sample....
4 KB (532 words) - 21:35, 24 February 2024
concept of "repeated sampling from the same population"; Neyman formulated confidence intervals and contributed heavily to sampling theory; Neyman and Pearson...
23 KB (2,521 words) - 17:53, 19 June 2024
sampling (also known as grab sampling, accidental sampling, or opportunity sampling) is a type of non-probability sampling that involves the sample being...
8 KB (983 words) - 03:38, 3 May 2024
finite population sampling, a sampling design specifies for every possible sample its probability of being drawn. Mathematically, a sampling design is denoted...
2 KB (290 words) - 09:02, 30 May 2021
sampling is also related to umbrella sampling in computational physics. Depending on the application, the term may refer to the process of sampling from...
25 KB (3,798 words) - 19:08, 4 June 2024
Top-p sampling avoids this by setting a threshold p and then restricting the sampling to the set of most probable tokens with cumulative probability less...
2 KB (251 words) - 23:25, 12 August 2024
Bernoulli sampling is therefore a special case of Poisson sampling. In Poisson sampling each element of the population may have a different probability of being...
4 KB (658 words) - 17:03, 27 May 2023
example, one can define a probability space which models the throwing of a die. A probability space consists of three elements: A sample space, Ω {\displaystyle...
24 KB (3,568 words) - 18:28, 16 July 2024
systematic sampling is a statistical method involving the selection of elements from an ordered sampling frame. The most common form of systematic sampling is...
6 KB (1,000 words) - 17:59, 13 May 2024
Binomial distribution (redirect from Binomial probability)
model the number of successes in a sample of size n drawn with replacement from a population of size N. If the sampling is carried out without replacement...
51 KB (7,517 words) - 21:15, 2 August 2024
specific sample size). A third possible solution is to use probability proportionate to size sampling. In this sampling plan, the probability of selecting...
16 KB (2,205 words) - 20:48, 3 March 2024