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  2. Faulty generalization - Wikipedia

    en.wikipedia.org/wiki/Faulty_generalization

    Hasty generalization is an informal fallacy of faulty generalization, which involves reaching an inductive generalization based on insufficient evidence [3] —essentially making a rushed conclusion without considering all of the variables or enough evidence.

  3. List of fallacies - Wikipedia

    en.wikipedia.org/wiki/List_of_fallacies

    Definitional retreat – changing the meaning of a word when an objection is raised. [23] Often paired with moving the goalposts (see below), as when an argument is challenged using a common definition of a term in the argument, and the arguer presents a different definition of the term and thereby demands different evidence to debunk the argument.

  4. List of cognitive biases - Wikipedia

    en.wikipedia.org/wiki/List_of_cognitive_biases

    Gerd Gigerenzer has criticized the framing of cognitive biases as errors in judgment, and favors interpreting them as arising from rational deviations from logical thought. [ 6 ] Explanations include information-processing rules (i.e., mental shortcuts), called heuristics , that the brain uses to produce decisions or judgments.

  5. Fallacy - Wikipedia

    en.wikipedia.org/wiki/Fallacy

    Errors of Reasoning: Naturalizing the Logic of Inference. London: College Publications. ISBN 978-1848901148; Fearnside, W. Ward and William B. Holther, Fallacy: The Counterfeit of Argument, 1959. [ISBN missing] Vincent F. Hendricks, Thought 2 Talk: A Crash Course in Reflection and Expression, New York: Automatic Press / VIP, 2005, ISBN 8799101378

  6. Errors and residuals - Wikipedia

    en.wikipedia.org/wiki/Errors_and_residuals

    For example, if the mean height in a population of 21-year-old men is 1.75 meters, and one randomly chosen man is 1.80 meters tall, then the "error" is 0.05 meters; if the randomly chosen man is 1.70 meters tall, then the "error" is −0.05 meters.

  7. Data cleansing - Wikipedia

    en.wikipedia.org/wiki/Data_cleansing

    Data cleansing or data cleaning is the process of identifying and correcting (or removing) corrupt, inaccurate, or irrelevant records from a dataset, table, or database.It involves detecting incomplete, incorrect, or inaccurate parts of the data and then replacing, modifying, or deleting the affected data. [1]

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    mail.aol.com

    Get AOL Mail for FREE! Manage your email like never before with travel, photo & document views. Personalize your inbox with themes & tabs. You've Got Mail!

  9. List of commonly misused English words - Wikipedia

    en.wikipedia.org/wiki/List_of_commonly_misused...

    Disect is an archaic word meaning "to separate by cutting", but has not been in common use since the 17th century. Standard: The Americas are bisected by the Panama canal. Standard: She dissected Smith's dissertation, pointing out scores of errors. Standard: We dissected the eye of a bull in biology class today.