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Digital dice = computational solutio...

Nahin, Paul J.

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Digital dice = computational solutions to practical probability problems /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Digital dice/ Paul J. Nahin.
其他題名:	computational solutions to practical probability problems /
作者:	Nahin, Paul J.
出版者:	Princeton, N.J. ;Princeton University Press, : c2008.,
面頁冊數:	1 online resource (xi, 263 p.) :ill.
內容註:	The clumsy dishwasher problem -- Will Lil and Bill meet at the malt shop? -- A parallel parking question -- A curious coin-flipping game -- The Gamow-Stern elevator puzzle -- Steve's elevator problem -- The pipe smoker's discovery -- A toilet paper dilemma -- The forgetful burglar problem -- The umbrella quandary -- The case of the missing senators -- How many runners in a marathon? -- A police patrol problem -- Parrondo's paradox -- How long is the wait to get the potato salad? -- The appeals court paradox -- Waiting for buses -- Waiting for stoplights -- Electing emperors and popes -- An optimal stopping problem -- Chain reactions, branching processes, and baby boys -- Appendixes: 1. One way to guess on a test -- 2. An example of variance-reduction in the Monte Carlo method -- 3. Random harmonic sums -- 4. Solving Montmort's problem by recursion -- 5. An illustration of the inclusion-exclusion principle -- 6. Solutions to the spin game -- 7. How to simulate Kelvin's fair coin with a biased coin -- 8. How to simulate an exponential random variable -- 9. Index to author-created MATLAB m-files in the book.
標題:	Probabilities -
電子資源:	http://www.jstor.org/stable/10.2307/j.ctt7rqgn
ISBN:	9781400839292 (electronic bk.)

Digital dice = computational solutions to practical probability problems /
Nahin, Paul J.

Digital dicecomputational solutions to practical probability problems /[electronic resource] :Paul J. Nahin. - Princeton, N.J. ;Princeton University Press,c2008. - 1 online resource (xi, 263 p.) :ill.

Includes bibliographical references and index.

The clumsy dishwasher problem -- Will Lil and Bill meet at the malt shop? -- A parallel parking question -- A curious coin-flipping game -- The Gamow-Stern elevator puzzle -- Steve's elevator problem -- The pipe smoker's discovery -- A toilet paper dilemma -- The forgetful burglar problem -- The umbrella quandary -- The case of the missing senators -- How many runners in a marathon? -- A police patrol problem -- Parrondo's paradox -- How long is the wait to get the potato salad? -- The appeals court paradox -- Waiting for buses -- Waiting for stoplights -- Electing emperors and popes -- An optimal stopping problem -- Chain reactions, branching processes, and baby boys -- Appendixes: 1. One way to guess on a test -- 2. An example of variance-reduction in the Monte Carlo method -- 3. Random harmonic sums -- 4. Solving Montmort's problem by recursion -- 5. An illustration of the inclusion-exclusion principle -- 6. Solutions to the spin game -- 7. How to simulate Kelvin's fair coin with a biased coin -- 8. How to simulate an exponential random variable -- 9. Index to author-created MATLAB m-files in the book.

AnnotationSome probability problems are so difficult that they stump the smartest mathematicians. But even the hardest of these problems can often be solved with a computer and a Monte Carlo simulation, in which a random-number generator simulates a physical process, such as a million rolls of a pair of dice. This is whatDigital Diceis all about: how to get numerical answers to difficult probability problems without having to solve complicated mathematical equations.Popular-math writer Paul Nahin challenges readers to solve twenty-one difficult but fun problems, from determining the odds of coin-flipping games to figuring out the behavior of elevators. Problems build from relatively easy (deciding whether a dishwasher who breaks most of the dishes at a restaurant during a given week is clumsy or just the victim of randomness) to the very difficult (tackling branching processes of the kind that had to be solved by Manhattan Project mathematician Stanislaw Ulam). In his characteristic style, Nahin brings the problems to life with interesting and odd historical anecdotes. Readers learn, for example, not just how to determine the optimal stopping point in any selection process but that astronomer Johannes Kepler selected his second wife by interviewing eleven women.The book shows readers how to write elementary computer codes using any common programming language, and provides solutions and line-by-line walk-throughs of a MATLAB code for each problem.Digital Dicewill appeal to anyone who enjoys popular math or computer science.

ISBN: 9781400839292 (electronic bk.)Subjects--Uniform Titles:

MATLAB.
Subjects--Topical Terms:

694044
Probabilities

LC Class. No.: QA273.25 / .N34 2011

Dewey Class. No.: 519.2076

Digital dice = computational solutions to practical probability problems /
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035 $a (OCoLC)730899250 $z (OCoLC)794554422
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082 0 4 $a 519.2076 $2 22
100 1 $a Nahin, Paul J. $3 1050654
245 1 0 $a Digital dice $h [electronic resource] : $b computational solutions to practical probability problems / $c Paul J. Nahin.
260 $a Princeton, N.J. ; $a Oxford : $b Princeton University Press, $c c2008.
300 $a 1 online resource (xi, 263 p.) : $b ill.
504 $a Includes bibliographical references and index.
505 0 $a The clumsy dishwasher problem -- Will Lil and Bill meet at the malt shop? -- A parallel parking question -- A curious coin-flipping game -- The Gamow-Stern elevator puzzle -- Steve's elevator problem -- The pipe smoker's discovery -- A toilet paper dilemma -- The forgetful burglar problem -- The umbrella quandary -- The case of the missing senators -- How many runners in a marathon? -- A police patrol problem -- Parrondo's paradox -- How long is the wait to get the potato salad? -- The appeals court paradox -- Waiting for buses -- Waiting for stoplights -- Electing emperors and popes -- An optimal stopping problem -- Chain reactions, branching processes, and baby boys -- Appendixes: 1. One way to guess on a test -- 2. An example of variance-reduction in the Monte Carlo method -- 3. Random harmonic sums -- 4. Solving Montmort's problem by recursion -- 5. An illustration of the inclusion-exclusion principle -- 6. Solutions to the spin game -- 7. How to simulate Kelvin's fair coin with a biased coin -- 8. How to simulate an exponential random variable -- 9. Index to author-created MATLAB m-files in the book.
520 8 $a Annotation $b Some probability problems are so difficult that they stump the smartest mathematicians. But even the hardest of these problems can often be solved with a computer and a Monte Carlo simulation, in which a random-number generator simulates a physical process, such as a million rolls of a pair of dice. This is whatDigital Diceis all about: how to get numerical answers to difficult probability problems without having to solve complicated mathematical equations.Popular-math writer Paul Nahin challenges readers to solve twenty-one difficult but fun problems, from determining the odds of coin-flipping games to figuring out the behavior of elevators. Problems build from relatively easy (deciding whether a dishwasher who breaks most of the dishes at a restaurant during a given week is clumsy or just the victim of randomness) to the very difficult (tackling branching processes of the kind that had to be solved by Manhattan Project mathematician Stanislaw Ulam). In his characteristic style, Nahin brings the problems to life with interesting and odd historical anecdotes. Readers learn, for example, not just how to determine the optimal stopping point in any selection process but that astronomer Johannes Kepler selected his second wife by interviewing eleven women.The book shows readers how to write elementary computer codes using any common programming language, and provides solutions and line-by-line walk-throughs of a MATLAB code for each problem.Digital Dicewill appeal to anyone who enjoys popular math or computer science.
588 $a Description based on print version record.
630 0 0 $a MATLAB. $3 532595
650 0 $a Probabilities $3 694044
650 0 $a Probabilities $x Data processing. $3 534352
650 0 $a Algorithms. $3 536374
856 4 0 $u http://www.jstor.org/stable/10.2307/j.ctt7rqgn