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Everything is predictable : how bayesian statistics explain our world / by Chivers, Tom(Science writer),author.(CARDINAL)889925;
Includes bibliographical references (pages 337-358) and index.An award-winning science writer shows how Bayes's theorem, which can predict the probability of an event, affects every aspect of our lives in fields as diverse as medicine, law and artificial intelligence.
Subjects: Statistical decision.; Bayesian statistical decision theory.;
Available copies: 3 / Total copies: 4
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Finitely additive probabilities and proper "improper" priors in Bayesian statistics / by Scozzafava, Romano.(CARDINAL)177139; University of North Carolina (System).Institute of Statistics.(CARDINAL)165205;
Includes bibliographical references (leaves [25]-[26]).
Subjects: Bayesian statistical decision theory.;
Available copies: 1 / Total copies: 2
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Bayesian statistics the fun way : understanding statistics and probability with Star Wars, LEGO, and Rubber Ducks / by Kurt, Will,author.;
"An introduction to Bayesian statistics with simple and pop culture-based explanations. Topics covered include measuring your own uncertainty in a belief, applying Bayes' theorem, and calculating distributions"--Part 1. Introduction to probability. Bayesian thinking and everyday reasoning -- Measuring uncertainty -- The logic of uncertainty -- Creating a binomial probability distribution -- The beta distribution -- Part 2. Bayesian probability and prior probabilities. Conditional probability -- Bayes' theorem with LEGO -- The prior, likelihood, and posterior of Bayes' theorem -- Bayesian priors and working with probability distributions -- Part 3. Parameter estimation. Introduction to averaging and parameter estimation -- Measuring the spread of our data -- The normal distribution -- Tools of parameter estimation : the PDF, CDF, and Quantile function -- Parameter estimation with prior probabilities -- Part 4. Hypothesis testing: the heart of statistics. From parameter estimation to hypothesis testing : building a Bayesian A/B test -- Introduction to the Bayes factor and posterior odds : the competition of ideas -- Bayesian reasoning in the twilight zone -- When data doesn't convince you -- From hypothesis testing to parameter estimation -- Appendix A: A quick introduction to R -- Appendix B: Enough calculus to get by.Part 1. Introduction to probability -- Ch. 1. Bayesian thinking and everyday reasoning -- Ch. 2. Measuring uncertainty -- Ch. 3. The logic of uncertainty -- Ch. 4. Creating a binomial probability distribution -- Ch. 5. The beta distribution -- Part 2. Bayesian probability and prior probabilities -- Ch. 6. Conditional probability -- Ch. 7. Bayes' theorem with LEGO -- Ch. 8. The prior, likelihood, and posterior of Bayes' theorem -- Ch. 9. Bayesian priors and working with probability distributions -- Part 3. Parameter estimation -- Ch. 10. Introduction to averaging and parameter estimation -- Ch. 11. Measuring the spread of our data -- Ch. 12. The normal distribution -- Ch. 13. Tools of parameter estimation : the PDF, CDF, and Quantile function -- Ch. 14. Parameter estimation with prior probabilities -- Part 4. Hypothesis testing : the heart of statistics -- Ch. 15. From parameter estimation to hypothesis testing : building a Bayesian A/B test -- Ch. 16. Introduction to the Bayes factor and posterior odds : the competition of ideas -- Ch. 17. Bayesian reasoning in the twilight zone -- Ch. 18. When data doesn't convince you -- Ch. 19. From hypothesis testing to parameter estimation -- Appendix A: A quick introduction to R -- Appendix B: Enough calculus to get by.
Subjects: Bayesian statistical decision theory.; Probabilities.;
Available copies: 1 / Total copies: 1
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The theory that would not die : how Bayes' rule cracked the enigma code, hunted down Russian submarines, & emerged triumphant from two centuries of controversy / by McGrayne, Sharon Bertsch.(CARDINAL)373334;
Includes bibliographical references (pages 275-306) and index.Enlightenment and the anti-Bayesian reaction. Causes in the air ; The man who did everything ; Many doubts, few defenders -- Second World War era. Bayes goes to war ; Dead and buried again -- The glorious revival. Arthur Bailey ; From tool to theology ; Jerome Cornfield, lung cancer, and heart attacks ; There's always a first time ; 46,656 varieties -- To prove its worth. Business decisions ; Who wrote The Federalist? The cold warrior ; Three Mile Island ; The Navy searches -- Victory. Eureka! ; Rosetta stones -- Appendixes. Dr. Fisher's casebook ; Applying Baye's Rule to mammograms and breast cancer."Bayes' rule appears to be a straightforward, one-line theorem: by updating our initial beliefs with objective new information, we get a new and improved belief. To its adherents, it is an elegant statement about learning from experience. To its opponents, it is subjectivity run amok. In the first-ever account of Bayes' rule for general readers, Sharon Bertsch McGrayne explores this controversial theorem and the human obsessions surrounding it. She traces its discovery by an amateur mathematician in the 1740s through its development into roughly its modern form by French scientist Pierre Simon Laplace. She reveals why respected statisticians rendered it professionally taboo for 150 years--at the same time that practitioners relied on it to solve crises involving great uncertainty and scanty information, even breaking Germany's Enigma code during World War II, and explains how the advent of off-the-shelf computer technology in the 1980s proved to be a game-changer. Today, Bayes' rule is used everywhere from DNA de-coding to Homeland Security. Drawing on primary source material and interviews with statisticians and other scientists, The Theory That Would Not Die is the riveting account of how a seemingly simple theorem ignited one of the greatest controversies of all time"--
Subjects: Bayesian statistical decision theory;
Available copies: 1 / Total copies: 1
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Non-existence of certain polynomial regressions in random sum theory / by Johnson, Norman Lloyd.(CARDINAL)146538; Kotz, Samuel.(CARDINAL)131116; University of North Carolina (System).Institute of Statistics.(CARDINAL)165205; University of North Carolina at Chapel Hill.Department of Statistics.(CARDINAL)149563;
Includes bibliographic references (page 6).
Subjects: Bayesian statistical decision theory.; Regression analysis.;
Available copies: 2 / Total copies: 3
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Bayes sequential testing : a direct and analytic approach / by Wu, Xizhi.(CARDINAL)182964; University of North Carolina (System).Institute of Statistics.(CARDINAL)165205; University of North Carolina at Chapel Hill.Department of Statistics.(CARDINAL)149563;
Includes bibliographical references (pages [109]-111).
Subjects: Bayesian statistical decision theory.; Sequential analysis.;
Available copies: 2 / Total copies: 3
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The Bayes rules for a clinical-trials model when the treatment responses are successes and failures / by Simons, Gordon.(CARDINAL)167686; University of North Carolina (System).Institute of Statistics.(CARDINAL)165205;
Includes bibliographical references (page [26]).
Subjects: Bayesian statistical decision theory.; Drugs;
Available copies: 1 / Total copies: 2
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The doomsday calculation : how an equation that predicts the future is transforming everything we know about life and the universe / by Poundstone, William,author.(CARDINAL)171005;
Includes bibliographical references (pages 265-295) and index.In the 18th century, the British minister and mathematician Thomas Bayes devised a theorem that allowed him to assign probabilities to events that had never happened before. It languished in obscurity for centuries until computers came along and made it easy to crunch the numbers. Now, as the foundation of big data, Bayes' formula has become a linchpin of the digital economy. But here's where things get really interesting: Bayes' theorem can also be used to lay odds on the existence of extraterrestrial intelligence; on whether we live in a Matrix-like counterfeit of reality; on the "many worlds" interpretation of quantum theory being correct; and on the biggest question of all: how long will humanity survive? The Doomsday Calculation tells how Silicon Valley's profitable formula became a controversial pivot of contemporary thought. Drawing on interviews with thought leaders around the globe, it's the story of a group of intellectual mavericks who are challenging what we thought we knew about our place in the universe. The Doomsday Calculation is compelling reading for anyone interested in our culture and its future.
Subjects: Bayesian statistical decision theory.; Probabilities.; Forecasting.;
Available copies: 4 / Total copies: 4
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Approximate Bayes model selection procedures for Markov random fields / by Seymour, Lynne.(CARDINAL)216939; Ji, Chuanshu.(CARDINAL)195643; University of North Carolina (System).Institute of Statistics.(CARDINAL)165205; University of North Carolina at Chapel Hill.Department of Statistics.(CARDINAL)149563;
Includes bibliographical references (pages 17-18).
Subjects: Bayesian statistical decision theory.; Markov random fields.;
Available copies: 2 / Total copies: 3
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A structured Bayesian approach to ARMA time series analysis. by Monahan, John F.(CARDINAL)170758; University of North Carolina (System).Institute of Statistics.(CARDINAL)165205;
Includes bibliographical references (leaf 5 (1st group)).
Subjects: Bayesian statistical decision theory.; Time-series analysis.;
Available copies: 1 / Total copies: 2
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Results 1 to 10 of 18 |