CLT: An Interactive Approach for Illustrating the Central Limit Theorem

dc.contributor.authorMakridakis, Spyros
dc.date.accessioned2015-12-08T09:10:29Z
dc.date.available2015-12-08T09:10:29Z
dc.date.issued1979-05
dc.description.abstractIn classical statistics, inferences about the popula- tion mean, confidence intervals, or testing of hypoth- eses are based on the sampling distribution of X. For the statistician or the mathematically sophisticated, there is little difficulty in proving the central limit theorem (CLT), namely, that the distribution of X can be approximated with a normal distribution whose mean is /ct and whose variance is -2/1n, as /? -> o. The majority of persons are unable to follow the proof, however, and most cannot understand what the CLT is or how it is used in classical statistics. This case is particularly true with students, even those students with strong mathematical backgrounds.en_UK
dc.doi10.2307/2683230
dc.identifier.issn0003-1305
dc.identifier.urihttp://hdl.handle.net/11728/6366
dc.language.isoenen_UK
dc.publisherTaylor & Francis, Ltd.en_UK
dc.relation.ispartofseriesThe American Statistician;Vol. 33, iss. 2
dc.rightsThe American Statistician, May 1979, Vol. 33, No. 2en_UK
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/en_UK
dc.subjectResearch Subject Categories::SOCIAL SCIENCES::Statistics, computer and systems science::Statisticsen_UK
dc.subjectResearch Subject Categories::SOCIAL SCIENCES::Business and economics::Economicsen_UK
dc.titleCLT: An Interactive Approach for Illustrating the Central Limit Theoremen_UK
dc.typeArticleen_UK

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