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- Type_I_and_type_II_errors abstract "In statistics, a null hypothesis is a statement that the thing being studied produces no effect or makes no difference. An example of a null hypothesis is the statement "This diet has no effect on people's weight." Usually an experimenter frames a null hypothesis with the intent of rejecting it: that is, intending to run an experiment which produces data that shows that the thing under study does make a difference.A type I error (or error of the first kind) is the incorrect rejection of a true null hypothesis. With respect to the non-null hypothesis, it represents a false positive. Usually a type I error leads one to conclude that a supposed effect or relationship exists when in fact it doesn't. Examples of type I errors include a test that shows a patient to have a disease when in fact the patient does not have the disease, a fire alarm going off indicating a fire when in fact there is no fire or an experiment indicating that a medical treatment should cure a disease when in fact it does not.A type II error (or error of the second kind) is the failure to reject a false null hypothesis. With respect to the non-null hypothesis, it represents a false negative. Examples of type II errors would be a blood test failing to detect the disease it was designed to detect, in a patient who really has the disease; a fire breaking out and the fire alarm does not ring or a clinical trial of a medical treatment failing to show that the treatment works when really it does.When comparing two means, concluding the means were different when in reality they were not different would be a Type I error; concluding the means were not different when in reality they were different would be a Type II error.All statistical hypothesis tests have a probability of making type I and type II errors. For example, all blood tests for a disease will falsely detect the disease in some proportion of people who don't have it, and will fail to detect the disease in some proportion of people who do have it. A test's probability of making a type I error is denoted by α. A test's probability of making a type II error is denoted by β.These terms are also used in a more general way by social scientists and others to refer to flaws in reasoning. This article is specifically devoted to the statistical meanings of those terms and the technical issues of the statistical errors that those terms describe.".
- Type_I_and_type_II_errors wikiPageExternalLink david.htm.
- Type_I_and_type_II_errors wikiPageExternalLink fullstory.
- Type_I_and_type_II_errors wikiPageExternalLink 18951.ppt.
- Type_I_and_type_II_errors wikiPageID "5657877".
- Type_I_and_type_II_errors wikiPageRevisionID "602597510".
- Type_I_and_type_II_errors hasPhotoCollection Type_I_and_type_II_errors.
- Type_I_and_type_II_errors subject Category:Design_of_experiments.
- Type_I_and_type_II_errors subject Category:Error.
- Type_I_and_type_II_errors subject Category:Hypothesis_testing.
- Type_I_and_type_II_errors subject Category:Spam_filtering.
- Type_I_and_type_II_errors comment "In statistics, a null hypothesis is a statement that the thing being studied produces no effect or makes no difference.".
- Type_I_and_type_II_errors label "Errores de tipo I y de tipo II".
- Type_I_and_type_II_errors label "Fout (statistiek)".
- Type_I_and_type_II_errors label "Type I and type II errors".
- Type_I_and_type_II_errors label "Ошибки первого и второго рода".
- Type_I_and_type_II_errors label "第一型及第二型錯誤".
- Type_I_and_type_II_errors label "第一種過誤と第二種過誤".
- Type_I_and_type_II_errors sameAs Chyby_typu_I_a_II.
- Type_I_and_type_II_errors sameAs Errores_de_tipo_I_y_de_tipo_II.
- Type_I_and_type_II_errors sameAs 第一種過誤と第二種過誤.
- Type_I_and_type_II_errors sameAs 1종_오류와_2종_오류.
- Type_I_and_type_II_errors sameAs Fout_(statistiek).
- Type_I_and_type_II_errors sameAs m.0dynqq.
- Type_I_and_type_II_errors sameAs Q1056324.
- Type_I_and_type_II_errors sameAs Q1056324.
- Type_I_and_type_II_errors wasDerivedFrom Type_I_and_type_II_errors?oldid=602597510.
- Type_I_and_type_II_errors isPrimaryTopicOf Type_I_and_type_II_errors.