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  2. Random assignment - Wikipedia

    en.wikipedia.org/wiki/Random_assignment

    Random assignment or random placement is an experimental technique for assigning human participants or animal subjects to different groups in an experiment (e.g., a treatment group versus a control group) using randomization, such as by a chance procedure (e.g., flipping a coin) or a random number generator. [1]

  3. Simple random sample - Wikipedia

    en.wikipedia.org/wiki/Simple_random_sample

    Survey methodology textbooks generally consider simple random sampling without replacement as the benchmark to compute the relative efficiency of other sampling approaches. [ 3 ] An unbiased random selection of individuals is important so that if many samples were drawn, the average sample would accurately represent the population.

  4. Reservoir sampling - Wikipedia

    en.wikipedia.org/wiki/Reservoir_sampling

    Reservoir sampling is a family of randomized algorithms for choosing a simple random sample, without replacement, of k items from a population of unknown size n in a single pass over the items. The size of the population n is not known to the algorithm and is typically too large for all n items to fit into main memory .

  5. Stratified randomization - Wikipedia

    en.wikipedia.org/wiki/Stratified_randomization

    Graphic breakdown of stratified random sampling. In statistics, stratified randomization is a method of sampling which first stratifies the whole study population into subgroups with same attributes or characteristics, known as strata, then followed by simple random sampling from the stratified groups, where each element within the same subgroup are selected unbiasedly during any stage of the ...

  6. Design effect - Wikipedia

    en.wikipedia.org/wiki/Design_effect

    Some of the more basic methods include simple random sampling (SRS, with or without replacement) and systematic sampling for getting a fixed sample size. There is also Bernoulli sampling with a random sample size. More advanced techniques such as stratified sampling and cluster sampling can also be designed to be EPSEM. For example, in cluster ...

  7. Latin hypercube sampling - Wikipedia

    en.wikipedia.org/wiki/Latin_hypercube_sampling

    Latin hypercube sampling (LHS) is a statistical method for generating a near-random sample of parameter values from a multidimensional distribution. The sampling method is often used to construct computer experiments or for Monte Carlo integration. [1] LHS was described by Michael McKay of Los Alamos National Laboratory in 1979. [1]

  8. Sample maximum and minimum - Wikipedia

    en.wikipedia.org/wiki/Sample_maximum_and_minimum

    The sample extrema can be used for a simple normality test, specifically of kurtosis: one computes the t-statistic of the sample maximum and minimum (subtracts sample mean and divides by the sample standard deviation), and if they are unusually large for the sample size (as per the three sigma rule and table therein, or more precisely a Student ...

  9. Pseudorandomness - Wikipedia

    en.wikipedia.org/wiki/Pseudorandomness

    Before modern computing, researchers requiring random numbers would either generate them through various means (dice, cards, roulette wheels, [5] etc.) or use existing random number tables. The first attempt to provide researchers with a ready supply of random digits was in 1927, when the Cambridge University Press published a table of 41,600 ...