The Theory of Probability
OUP Oxford, 6 sie 1998 - 470
Another title in the reissued Oxford Classic Texts in the Physical Sciences series, Jeffrey's Theory of Probability, first published in 1939, was the first to develop a fundamental theory of scientific inference based on the ideas of Bayesian statistics. His ideas were way ahead of their time and it is only in the past ten years that the subject of Bayes' factors has been significantly developed and extended. Until recently the two schools of statistics (Bayesian and Frequentist) were distinctly different and set apart. Recent work (aided by increased computer power and availability) has changed all that and today's graduate students and researchers all require an understanding of Bayesian ideas. This book is their starting point.
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APPROXIMATE METHODS AND SIMPLIFICATIONS
SIGNIFICANCE TESTS ONE NEW PARAMETER
SIGNIFICANCE TESTS VARIOUS COMPLICATIONS
FREQUENCY DEFINITIONS AND DIRECT METHODS
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accuracy actual alternatives applied approximation argument arise assessment Axiom Bernoulli's theorem binomial chance coefficient consider convenient corresponding definition degrees of freedom departure derived E. S. Pearson earthquake equal expectation express fact factor finite Fisher follows function give given Hence independent induction inference infinite number intervals intraclass correlation inverse probability large number law of error limit location parameter logic mathematical maximum likelihood mean method normal correlation normal equations normal law null hypothesis number of observations Pearson Poisson positive possible values posterior probability postulates prior probability prior probability distribution probability distribution product rule proposition random range ratio rejected residuals result rule sample set of observations significance test solution square standard error statement sufficient statistics suggested suppose systematic error theorem theory tion true value uncertainty uniform distribution unknown usually variable variation zero