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2. Sampling (statistics) - Wikipedia

   en.wikipedia.org/wiki/Sampling_(statistics)

   Panel sampling is the method of first selecting a group of participants through a random sampling method and then asking that group for (potentially the same) information several times over a period of time. Therefore, each participant is interviewed at two or more time points; each period of data collection is called a "wave".

3. Survey sampling - Wikipedia

   en.wikipedia.org/wiki/Survey_sampling

   The other books focus on the statistical theory of survey sampling and require some knowledge of basic statistics, as discussed in the following textbooks: David S. Moore and George P. McCabe (February 2005). "Introduction to the practice of statistics" (5th edition). W.H. Freeman & Company. ISBN 0-7167-6282-X.

4. Monte Carlo method - Wikipedia

   en.wikipedia.org/wiki/Monte_Carlo_method

   Sawilowsky [56] distinguishes between a simulation, a Monte Carlo method, and a Monte Carlo simulation: a simulation is a fictitious representation of reality, a Monte Carlo method is a technique that can be used to solve a mathematical or statistical problem, and a Monte Carlo simulation uses repeated sampling to obtain the statistical ...

5. Oversampling and undersampling in data analysis - Wikipedia

   en.wikipedia.org/wiki/Oversampling_and_under...

   Within statistics, oversampling and undersampling in data analysis are techniques used to adjust the class distribution of a data set (i.e. the ratio between the different classes/categories represented). These terms are used both in statistical sampling, survey design methodology and in machine learning.

6. Inverse transform sampling - Wikipedia

   en.wikipedia.org/wiki/Inverse_transform_sampling

   Inverse transform sampling (also known as inversion sampling, the inverse probability integral transform, the inverse transformation method, or the Smirnov transform) is a basic method for pseudo-random number sampling, i.e., for generating sample numbers at random from any probability distribution given its cumulative distribution function.

7. 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 ...

8. Systematic sampling - Wikipedia

   en.wikipedia.org/wiki/Systematic_sampling

   In one-dimensional systematic sampling, progression through the list is treated circularly, with a return to the top once the list ends. The sampling starts by selecting an element from the list at random and then every k th element in the frame is selected, where k, is the sampling interval (sometimes known as the skip): this is calculated as: [3]

9. Simple random sample - Wikipedia

   en.wikipedia.org/wiki/Simple_random_sample

   This means that every student in the school has in any case approximately a 1 in 10 chance of being selected using this method. Further, any combination of 100 students has the same probability of selection. If a systematic pattern is introduced into random sampling, it is referred to as "systematic (random) sampling".