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  2. Rejection sampling - Wikipedia

    en.wikipedia.org/wiki/Rejection_sampling

    Rejection sampling. In numerical analysis and computational statistics, rejection sampling is a basic technique used to generate observations from a distribution. It is also commonly called the acceptance-rejection method or "accept-reject algorithm" and is a type of exact simulation method. The method works for any distribution in with a density .

  3. Refusal of work - Wikipedia

    en.wikipedia.org/wiki/Refusal_of_work

    Politics portal. v. t. e. Refusal of work is behavior in which a person refuses regular employment. [1] As actual behavior, with or without a political or philosophical program, it has been practiced by various subcultures and individuals. It is frequently engaged in by those who critique the concept of work, and it has a long history.

  4. Secretary problem - Wikipedia

    en.wikipedia.org/wiki/Secretary_problem

    Secretary problem. Graphs of probabilities of getting the best candidate (red circles) from n applications, and k / n (blue crosses) where k is the sample size. The secretary problem demonstrates a scenario involving optimal stopping theory [1] [2] that is studied extensively in the fields of applied probability, statistics, and decision theory ...

  5. Don't Get Crushed By Job Rejection - AOL

    www.aol.com/news/2013-02-05-job-rejection...

    By Alison Green Getting rejected for a job you really wanted is one of the worst parts of job searching. But if you handle the rejection well, you can get something useful out of the disappointment.

  6. Acceptance sampling - Wikipedia

    en.wikipedia.org/wiki/Acceptance_sampling

    [1] In general, acceptance sampling is employed when one or several of the following hold: [2] testing is destructive; the cost of 100% inspection is very high; and; 100% inspection takes too long. A wide variety of acceptance sampling plans is available. For example, multiple sampling plans use more than two samples to reach a conclusion.

  7. Type I and type II errors - Wikipedia

    en.wikipedia.org/wiki/Type_I_and_type_II_errors

    In statistical hypothesis testing, a type I error, or a false positive, is the rejection of the null hypothesis when it is actually true. For example, an innocent person may be convicted. A type II error, or a false negative, is the failure to reject a null hypothesis that is actually false. For example: a guilty person may be not convicted.

  8. Right of first refusal - Wikipedia

    en.wikipedia.org/wiki/Right_of_first_refusal

    Right of first refusal (ROFR or RFR) is a contractual right that gives its holder the option to enter a business transaction with the owner of something, according to specified terms, before the owner is entitled to enter into that transaction with a third party. A first refusal right must have at least three parties: the owner, the third party ...

  9. False positives and false negatives - Wikipedia

    en.wikipedia.org/wiki/False_positives_and_false...

    The specificity of the test is equal to 1 minus the false positive rate. [7] In statistical hypothesis testing, this fraction is given the Greek letter α, and 1 − α is defined as the specificity of the test. Increasing the specificity of the test lowers the probability of type I errors, but may raise the probability of type II errors (false ...