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  2. Selection bias - Wikipedia

    en.wikipedia.org/wiki/Selection_bias

    Selection bias is the bias introduced by the selection of individuals, groups, or data for analysis in such a way that proper randomization is not achieved, thereby failing to ensure that the sample obtained is representative of the population intended to be analyzed. [1] It is sometimes referred to as the selection effect.

  3. Total survey error - Wikipedia

    en.wikipedia.org/wiki/Total_survey_error

    Sampling error, which occurs in sample surveys but not censuses results from the variability inherent in using a randomly selected fraction of the population for estimation. Nonsampling error, which occurs in surveys and censuses alike, is the sum of all other errors, including errors in frame construction, sample selection, data collection ...

  4. Sampling error - Wikipedia

    en.wikipedia.org/wiki/Sampling_error

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  5. Sampling bias - Wikipedia

    en.wikipedia.org/wiki/Sampling_bias

    Sampling bias can lead to a systematic over- or under-estimation of the corresponding parameter in the population. Sampling bias occurs in practice as it is practically impossible to ensure perfect randomness in sampling. If the degree of misrepresentation is small, then the sample can be treated as a reasonable approximation to a random sample.

  6. Randomization - Wikipedia

    en.wikipedia.org/wiki/Randomization

    Randomization is a statistical process in which a random mechanism is employed to select a sample from a population or assign subjects to different groups. [1] [2] [3] The process is crucial in ensuring the random allocation of experimental units or treatment protocols, thereby minimizing selection bias and enhancing the statistical validity. [4]

  7. Sampling (statistics) - Wikipedia

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

    A visual representation of the sampling process. In statistics, quality assurance, and survey methodology, sampling is the selection of a subset or a statistical sample (termed sample for short) of individuals from within a statistical population to estimate characteristics of the whole population.

  8. Randomness - Wikipedia

    en.wikipedia.org/wiki/Randomness

    By analogy, quasi-Monte Carlo methods use quasi-random number generators. Random selection, when narrowly associated with a simple random sample, is a method of selecting items (often called units) from a population where the probability of choosing a specific item is the proportion of those items in the population. For example, with a bowl ...

  9. Randomized experiment - Wikipedia

    en.wikipedia.org/wiki/Randomized_experiment

    In the statistical theory of design of experiments, randomization involves randomly allocating the experimental units across the treatment groups.For example, if an experiment compares a new drug against a standard drug, then the patients should be allocated to either the new drug or to the standard drug control using randomization.