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Who's #1? : The Science of Rating and Ranking /
"Who's #1? offers an engaging and accessible account of how scientific rating and ranking methods are created and applied to a variety of uses. Amy Langville and Carl Meyer provide the first comprehensive overview of the mathematical algorithms and methods used to rate and rank sports team...
| Autores principales: | , |
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| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Princeton [N.J.] :
Princeton University Press,
2012.
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| Colección: | Book collections on Project MUSE.
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| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 008 | 120109s2012 nju o 00 0 eng d | ||
| 010 | |z 2011036016 | ||
| 020 | |a 9781400841677 | ||
| 020 | |z 9780691162317 | ||
| 020 | |z 9780691154220 | ||
| 035 | |a (OCoLC)812416886 | ||
| 040 | |a MdBmJHUP |c MdBmJHUP | ||
| 100 | 1 | |a Langville, Amy N., |e author. | |
| 245 | 1 | 0 | |a Who's #1? : |b The Science of Rating and Ranking / |c Amy N. Langville and Carl D. Meyer. |
| 264 | 1 | |a Princeton [N.J.] : |b Princeton University Press, |c 2012. | |
| 264 | 3 | |a Baltimore, Md. : |b Project MUSE, |c 2016 | |
| 264 | 4 | |c ©2012. | |
| 300 | |a 1 online resource (272 pages): |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 505 | 0 | 0 | |t Introduction to ranking -- |t Massey's method -- |t Colley's method -- |t Keener's method -- |t Elo's system -- |t The Markov method -- |t The offense-defense rating method -- |t Ranking by reordering methods -- |t Point spreads -- |t User preference ratings -- |t Handling ties -- |t Incorporating weights -- |t "What if -- " scenarios and sensitivity -- |t Rank aggregation : part 1 -- |t Rank aggregation : part 2 -- |t Methods of comparison -- |t Data -- |g Epilogue. |
| 520 | |a "Who's #1? offers an engaging and accessible account of how scientific rating and ranking methods are created and applied to a variety of uses. Amy Langville and Carl Meyer provide the first comprehensive overview of the mathematical algorithms and methods used to rate and rank sports teams, political candidates, products, Web pages, and more. In a series of interesting asides, Langville and Meyer provide fascinating insights into the ingenious contributions of many of the field's pioneers. They survey and compare the different methods employed today, showing why their strengths and weaknesses depend on the underlying goal, and explaining why and when a given method should be considered. Also describe what can and can't be expected from the most widely used systems"-- |c Provided by publisher. | ||
| 546 | |a English. | ||
| 588 | |a Description based on print version record. | ||
| 650 | 7 | |a Ranking and selection (Statistics) |2 fast |0 (OCoLC)fst01089915 | |
| 650 | 7 | |a Mathematics. |2 eflch | |
| 650 | 7 | |a MATHEMATICS |x Counting & Numeration. |2 bisacsh | |
| 650 | 7 | |a MATHEMATICS |x Probability & Statistics |x General. |2 bisacsh | |
| 650 | 6 | |a Rang et selection (Statistique) | |
| 650 | 4 | |a Ranking and selection (Statistics) | |
| 650 | 0 | |a Ranking and selection (Statistics) | |
| 655 | 7 | |a Electronic books. |2 local | |
| 700 | 1 | |a Meyer, C. D. |q (Carl Dean), |e author. | |
| 710 | 2 | |a Project Muse. |e distributor | |
| 830 | 0 | |a Book collections on Project MUSE. | |
| 880 | 0 | |6 505-00/(S |a Cover -- Contents -- Preface -- Purpose -- Audience -- Prerequisites -- Teaching from This Book -- Acknowledgments -- Chapter 1. Introduction to Ranking -- Social Choice and Arrow's Impossibility Theorem -- Arrow's Impossibility Theorem -- Small Running Example -- Chapter 2. Massey's Method -- Initial Massey Rating Method -- Massey's Main Idea -- The Running Example Using the Massey Rating Method -- Advanced Features of the Massey Rating Method -- The Running Example: Advanced Massey Rating Method -- Summary of the Massey Rating Method -- Chapter 3. Colley's Method -- The Running Example -- Summary of the Colley Rating Method -- Connection between Massey and Colley Methods -- Chapter 4. Keener's Method -- Strength and Rating Stipulations -- Selecting Strength Attributes -- Laplace's Rule of Succession -- To Skew or Not to Skew-- Normalization -- Chicken or Egg-- Ratings -- Strength -- The Keystone Equation -- Constraints -- Perron-Frobenius -- Important Properties -- Computing the Ratings Vector -- Forcing Irreducibility and Primitivity -- Summary -- The 2009-2010 NFL Season -- Jim Keener vs. Bill James -- Back to the Future -- Can Keener Make You Rich-- Conclusion -- Chapter 5. Elo's System -- Elegant Wisdom -- The K-Factor -- The Logistic Parameter ξ -- Constant Sums -- Elo in the NFL -- Hindsight Accuracy -- Foresight Accuracy -- Incorporating Game Scores -- Hindsight and Foresight with Ŧ = 1000, K = 32, H = 15 -- Using Variable K-Factors with NFL Scores -- Hindsight and Foresight Using Scores and Variable K-Factors -- Game-by-Game Analysis -- Conclusion -- Chapter 6. The Markov Method -- The Markov Method -- Voting with Losses -- Losers Vote with Point Differentials -- Winners and Losers Vote with Points -- Beyond Game Scores -- Handling Undefeated Teams -- Summary of the Markov Rating Method. | |
| 856 | 4 | 0 | |z Texto completo |u https://projectmuse.uam.elogim.com/book/36410/ |
| 945 | |a Project MUSE - Custom Collection | ||
| 945 | |a Project MUSE - Archive Complete Supplement IV | ||