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  2. Glossary of probability and statistics - Wikipedia

    en.wikipedia.org/wiki/Glossary_of_probability...

    An example is the average test score of a subset of 10 students from a class. On the assumption that the sample is representative of the larger population, the sample mean is often used as an estimator of the population mean, which in this example would be the average test score of all of the students in the class. sample space

  3. Sampling (statistics) - Wikipedia

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

    A simple example would be to select every 10th name from the telephone directory (an 'every 10th' sample, also referred to as 'sampling with a skip of 10'). As long as the starting point is randomized, systematic sampling is a type of probability sampling.

  4. Simple random sample - Wikipedia

    en.wikipedia.org/wiki/Simple_random_sample

    An example would be if the students in the school had numbers attached to their names ranging from 0001 to 1000, and we chose a random starting point, e.g. 0533, and then picked every 10th name thereafter to give us our sample of 100 (starting over with 0003 after reaching 0993).

  5. Systematic sampling - Wikipedia

    en.wikipedia.org/wiki/Systematic_sampling

    This is random sampling with a system. From the sampling frame, a starting point is chosen at random, and choices thereafter are at regular intervals. For example, suppose you want to sample 8 houses from a street of 120 houses. 120/8=15, so every 15th house is chosen after a random starting point between 1 and 15.

  6. Reservoir sampling - Wikipedia

    en.wikipedia.org/wiki/Reservoir_sampling

    Suppose we see a sequence of items, one at a time. We want to keep 10 items in memory, and we want them to be selected at random from the sequence. If we know the total number of items n and can access the items arbitrarily, then the solution is easy: select 10 distinct indices i between 1 and n with equal probability, and keep the i-th

  7. Oversampling and undersampling in data analysis - Wikipedia

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

    The feature space for the minority class for which we want to oversample could be beak length, wingspan, and weight (all continuous). To then oversample, take a sample from the dataset, and consider its k nearest neighbors (in feature space). To create a synthetic data point, take the vector between one of those k neighbors, and the current ...

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  9. Sample space - Wikipedia

    en.wikipedia.org/wiki/Sample_space

    A sample space is usually denoted using set notation, and the possible ordered outcomes, or sample points, [5] are listed as elements in the set. It is common to refer to a sample space by the labels S, Ω, or U (for "universal set"). The elements of a sample space may be numbers, words, letters, or symbols.

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