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dc.contributor.authorSenn, Stephen
dc.date.accessioned2021-12-08T21:01:59Z
dc.date.available2021-12-08T21:01:59Z
dc.date.issued2011
dc.identifier.urihttps://jlupub.ub.uni-giessen.de//handle/jlupub/445
dc.identifier.urihttp://dx.doi.org/10.22029/jlupub-378
dc.description.abstractAn elementary sketch of some issues in statistical inference and in particular of the central role of likelihood is given. This is followed by brief outlines of what George Barnard considered were the four great systems of statistical inferences. These can be thought of terms of the four combinations of two factors at two levels. The first is fundamental purpose (decision or inference) and the second probability argument (direct or inverse). Of these four systems the `fully Bayesian' approach of decision-making using inverse probability particularly associated with the Ramsay, De Finetti, Savage and Lindley has some claims to be the most impressive. It is claimed, however, and illustrated by example, that this approach seems to be impossible to follow. It is speculated that there may be some advantage to the practising statistician to follow George Barnard's advice of being familiar with all four systems.de_DE
dc.language.isoende_DE
dc.subject.ddcddc:100de_DE
dc.subject.ddcddc:330de_DE
dc.titleYou May Believe You Are a Bayesian But You Are Probably Wrongde_DE
dc.typearticlede_DE
dcterms.isPartOf2536124-7
local.affiliationExterne Einrichtungende_DE
local.source.spage48de_DE
local.source.epage66de_DE
local.source.journaltitleRationality, markets, and morals: RMMde_DE
local.source.volume2de_DE


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