A Statistical approach to predict future members of the Baseball Hall of Fame

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dc.contributor.advisorMarshall, David, Ph. D.en_US
dc.contributor.advisorHamner, Mark S.en_US
dc.contributor.advisorEdwards, Don E.en_US
dc.contributor.advisorNavarra-Madsen, Junalynen_US
dc.contributor.authorZemler, Kelseyen_US
dc.date.accessioned2014-12-05T17:36:34Z
dc.date.available2014-12-05T17:36:34Z
dc.date.copyright2013en_US
dc.date.issued1/1/2013en_US
dc.description.abstractThe purpose of this study was to construct an accurate statistical model for the members of the baseball hall of fame and use this model to predict future hall of fame members, using a frequentist approach. Using logistic regression, accurate models were determined for each position that can be used to predict if a certain player will make it into the Hall of Fame. Baseball-Reference.com was the major source of data. Once the analysis was complete, nine different models were chosen to determine the probability that a certain player at a given position would make it into the Hall of Fame based on their baseball statistics. Positions were also analyzed by time periods and models were found for each position in each time frame, if one existed. In general, time period models for the various positions were inconclusive, however a model for each position was found overall.en_US
dc.identifier.urihttp://hdl.handle.net/11274/3596
dc.language.isoen_USen_US
dc.publisherTexas Woman s Universityen_US
dc.subjectMathematicsen_US
dc.subjectStatisticsen_US
dc.titleA Statistical approach to predict future members of the Baseball Hall of Fameen_US
dc.typeThesisen_US

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