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  2. Type III error - Wikipedia

    en.wikipedia.org/wiki/Type_III_error

    In the 2009 book Dirty rotten strategies by Ian I. Mitroff and Abraham Silvers described type III and type IV errors providing many examples of both developing good answers to the wrong questions (III) and deliberately selecting the wrong questions for intensive and skilled investigation (IV). Most of the examples have nothing to do with ...

  3. Gambler's fallacy - Wikipedia

    en.wikipedia.org/wiki/Gambler's_fallacy

    The gambler's fallacy, also known as the Monte Carlo fallacy or the fallacy of the maturity of chances, is the belief that, if an event (whose occurrences are independent and identically distributed) has occurred less frequently than expected, it is more likely to happen again in the future (or vice versa).

  4. Type I and type II errors - Wikipedia

    en.wikipedia.org/wiki/Type_I_and_type_II_errors

    The probability of type I errors is called the "false reject rate" (FRR) or false non-match rate (FNMR), while the probability of type II errors is called the "false accept rate" (FAR) or false match rate (FMR). If the system is designed to rarely match suspects then the probability of type II errors can be called the "false alarm rate". On the ...

  5. Probability of error - Wikipedia

    en.wikipedia.org/wiki/Probability_of_error

    This statistics -related article is a stub. You can help Wikipedia by expanding it.

  6. False positives and false negatives - Wikipedia

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

    The false positive rate (FPR) is the proportion of all negatives that still yield positive test outcomes, i.e., the conditional probability of a positive test result given an event that was not present. The false positive rate is equal to the significance level. The specificity of the test is equal to 1 minus the false positive rate.

  7. Confusion of the inverse - Wikipedia

    en.wikipedia.org/wiki/Confusion_of_the_inverse

    Confusion of the inverse, also called the conditional probability fallacy or the inverse fallacy, is a logical fallacy whereupon a conditional probability is equated with its inverse; that is, given two events A and B, the probability of A happening given that B has happened is assumed to be about the same as the probability of B given A, when there is actually no evidence for this assumption.

  8. Misuse of statistics - Wikipedia

    en.wikipedia.org/wiki/Misuse_of_statistics

    A seemingly simple question about the number of words in the English language immediately encounters questions about archaic forms, accounting for prefixes and suffixes, multiple definitions of a word, variant spellings, dialects, fanciful creations (like ectoplastistics from ectoplasm and statistics), [10] technical vocabulary, and so on.

  9. Monte Carlo algorithm - Wikipedia

    en.wikipedia.org/wiki/Monte_carlo_algorithm

    Thus, if the number is prime then the answer is always correct, and if the number is composite then the answer is correct with probability at least 1−(1− 1 ⁄ 2) k = 1−2 −k. For Monte Carlo decision algorithms with two-sided error, the failure probability may again be reduced by running the algorithm k times and returning the majority ...

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