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In 1865, Gregor Mendel presented \u201cExperiments in
Plant-Hybridization,\u201d the results of his eight-year study of
the principles of inheritance through experimentation with pea
plants. Overlooked in its day, Mendel's work would later become the
foundation of modern genetics. Did his pioneering research follow
the rigors of real scientific inquiry, or was Mendel's data too
good to be true-the product of doctored statistics? In Ending the
Mendel-Fisher Controversy, leading experts present their
conclusions on the legendary controversy surrounding the challenge
to Mendel's findings by British statistician and biologist R. A.
Fisher. In his 1936 paper \u201cHas Mendel's Work Been
Rediscovered?\u201d Fisher suggested that Mendel's data could have
been falsified in order to support his expectations. Fisher
attributed the falsification to an unknown assistant of Mendel's.
At the time, Fisher's criticism did not receive wide attention. Yet
beginning in 1964, about the time of the centenary of Mendel's
paper, scholars began to publicly discuss whether Fisher had
successfully proven that Mendel's data was falsified. Since that
time, numerous articles, letters, and comments have been published
on the controversy. This self-contained volume includes everything
the reader will need to know about the subject: an overview of the
controversy; the original papers of Mendel and Fisher; four of the
most important papers on the debate; and new updates, by the
authors, of the latter four papers. Taken together, the authors
contend, these voices argue for an end to the controversy-making
this book the definitive last word on the subject.
This important collection of essays is a synthesis of foundational studies in Bayesian decision theory and statistics. An overarching topic of the collection is understanding how the norms for Bayesian decision making should apply in settings with more than one rational decision maker and then tracing out some of the consequences of this turn for Bayesian statistics. The volume will be particularly valuable to philosophers concerned with decision theory, probability, and statistics, statisticians, mathematicians, and economists.
This important collection of essays is a synthesis of foundational
studies in Bayesian decision theory and statistics. An overarching
topic of the collection is understanding how the norms for Bayesian
decision making should apply in settings with more than one
rational decision maker and then tracing out some of the
consequences of this turn for Bayesian statistics. There are four
principal themes to the collection: cooperative, non-sequential
decisions; the representation and measurement of 'partially
ordered' preferences; non-cooperative, sequential decisions; and
pooling rules and Bayesian dynamics for sets of probabilities. The
volume will be particularly valuable to philosophers concerned with
decision theory, probability, and statistics, statisticians,
mathematicians, and economists.
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