Isbn: 9781107603578 - Bayesian Cognitive Modeling: a Practical Course (20 results)

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  • Language: English

    Published by Cambridge University Press, 2014

    1107603579 / 9781107603578

    • Softcover

    Seller: MERS Goodwill, Saint Louis, MO, U.S.A.MERS Goodwill

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    Condition: good. Used - Good: All pages and cover are intact including the dust cover, if applicable . Spine may show signs of wear. Pages may include limited notes and highlighting. May include From the library of labels. Shrink wrap, dust covers, or boxed set case may be missing. Item may be missing bundled media. Any access codes or passwords originally included with the book may be expired, used or no longer valid. Image is stock photo and cover art edition may be different than pictured.

  • Language: English

    Published by Cambridge University Press, 2014

    1107603579 / 9781107603578

    • Softcover

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    Condition: good. Befriedigend/Good: Durchschnittlich erhaltenes Buch bzw. Schutzumschlag mit Gebrauchsspuren, aber vollständigen Seiten. / Describes the average WORN book or dust jacket that has all the pages present.

  • Language: English

    Published by Cambridge University Press, 2014

    1107603579 / 9781107603578

    • Softcover

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  • Language: English

    Published by Cambridge University Press, 2014

    1107603579 / 9781107603578

    • Softcover

    Seller: California Books, Miami, FL, U.S.A.California Books

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  • Language: English

    Published by Cambridge University Press, GB, 2014

    1107603579 / 9781107603578

    • Softcover

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    Paperback. Condition: New. Bayesian inference has become a standard method of analysis in many fields of science. Students and researchers in experimental psychology and cognitive science, however, have failed to take full advantage of the new and exciting possibilities that the Bayesian approach affords. Ideal for teaching and self study, this book demonstrates how to do Bayesian modeling. Short, to-the-point chapters offer examples, exercises, and computer code (using WinBUGS or JAGS, and supported by Matlab and R), with additional support available online. No advance knowledge of statistics is required and, from the very start, readers are encouraged to apply and adjust Bayesian analyses by themselves. The book contains a series of chapters on parameter estimation and model selection, followed by detailed case studies from cognitive science. After working through this book, readers should be able to build their own Bayesian models, apply the models to their own data, and draw their own conclusions.

  • Language: English

    Published by Cambridge University Press, 2014

    1107603579 / 9781107603578

    • Softcover

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  • Language: English

    Published by Cambridge University Press, 2014

    1107603579 / 9781107603578

    • Softcover

    Seller: Ria Christie Collections, Uxbridge, United KingdomRia Christie Collections

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  • Language: English

    Published by Cambridge University Press, 2014

    1107603579 / 9781107603578

    • Softcover

    Seller: GreatBookPricesUK, Woodford Green, United KingdomGreatBookPricesUK

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  • Language: English

    Published by Cambridge University Press, 2014

    1107603579 / 9781107603578

    • Softcover

    Seller: GreatBookPricesUK, Woodford Green, United KingdomGreatBookPricesUK

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  • Language: English

    Published by Cambridge University Press CUP, 2014

    1107603579 / 9781107603578

    • Softcover

    Seller: Books Puddle, New York, NY, U.S.A.Books Puddle

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    Condition: New. pp. 284.

  • Language: English

    Published by Cambridge Univ Pr, 2014

    1107603579 / 9781107603578

    • Softcover

    Seller: Revaluation Books, Exeter, United KingdomRevaluation Books

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    Paperback. Condition: Brand New. 264 pages. 9.75x7.50x0.50 inches. In Stock.

  • Language: English

    Published by Cambridge University Press, 2014

    1107603579 / 9781107603578

    • Softcover

    Seller: Kennys Bookstore, Olney, MD, U.S.A.Kennys Bookstore

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    Condition: New. Using a practical, hands-on approach, this book will teach anyone how to carry out Bayesian analyses and interpret the results. Num Pages: 284 pages. BIC Classification: JMH; JMR; PBWH. Category: (P) Professional & Vocational. Dimension: 245 x 188 x 16. Weight in Grams: 548. . 2014. Paperback. . . . . Books ship from the US and Ireland.

  • Language: English

    Published by Cambridge University Press, 2014

    1107603579 / 9781107603578

    • Softcover

    Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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    Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Bayesian inference has become a standard method of analysis in many fields of science. Students and researchers in experimental psychology and cognitive science, however, have failed to take full advantage of the new and exciting possibilities that the Bayesian approach affords. Ideal for teaching and self study, this book demonstrates how to do Bayesian modeling. Short, to-the-point chapters offer examples, exercises, and computer code (using WinBUGS or JAGS, and supported by Matlab and R), with additional support available online. No advance knowledge of statistics is required and, from the very start, readers are encouraged to apply and adjust Bayesian analyses by themselves. The book contains a series of chapters on parameter estimation and model selection, followed by detailed case studies from cognitive science. After working through this book, readers should be able to build their own Bayesian models, apply the models to their own data, and draw their own conclusions.

  • Language: English

    Published by Cambridge University Press, 2014

    1107603579 / 9781107603578

    • Softcover

    Seller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, IrelandKennys Bookshop and Art Galleries Ltd.

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    Condition: New. Using a practical, hands-on approach, this book will teach anyone how to carry out Bayesian analyses and interpret the results. Num Pages: 284 pages. BIC Classification: JMH; JMR; PBWH. Category: (P) Professional & Vocational. Dimension: 245 x 188 x 16. Weight in Grams: 548. . 2014. Paperback. . . . .

  • Language: English

    Published by Cambridge University Press, GB, 2014

    1107603579 / 9781107603578

    • Softcover

    Seller: Rarewaves.com UK, London, United KingdomRarewaves.com UK

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    Paperback. Condition: New. Bayesian inference has become a standard method of analysis in many fields of science. Students and researchers in experimental psychology and cognitive science, however, have failed to take full advantage of the new and exciting possibilities that the Bayesian approach affords. Ideal for teaching and self study, this book demonstrates how to do Bayesian modeling. Short, to-the-point chapters offer examples, exercises, and computer code (using WinBUGS or JAGS, and supported by Matlab and R), with additional support available online. No advance knowledge of statistics is required and, from the very start, readers are encouraged to apply and adjust Bayesian analyses by themselves. The book contains a series of chapters on parameter estimation and model selection, followed by detailed case studies from cognitive science. After working through this book, readers should be able to build their own Bayesian models, apply the models to their own data, and draw their own conclusions.

  • Language: English

    Published by Cambridge University Press, 2014

    1107603579 / 9781107603578

    • Softcover
    • Print on Demand

    Seller: THE SAINT BOOKSTORE, Southport, United KingdomTHE SAINT BOOKSTORE

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    Paperback / softback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.

  • Language: English

    Published by Cambridge University Press, 2014

    1107603579 / 9781107603578

    • Softcover
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    Seller: Majestic Books, Hounslow, United KingdomMajestic Books

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    Condition: New. Print on Demand pp. 284.

  • Language: English

    Published by Cambridge University Press, 2014

    1107603579 / 9781107603578

    • Softcover
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    Seller: Biblios, frankfurt am main, HESSE, GermanyBiblios

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    Condition: New. PRINT ON DEMAND pp. 284.

  • Language: English

    Published by Cambridge University Press, Cambridge, 2014

    1107603579 / 9781107603578

    • Softcover
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    Paperback. Condition: new. Paperback. Bayesian inference has become a standard method of analysis in many fields of science. Students and researchers in experimental psychology and cognitive science, however, have failed to take full advantage of the new and exciting possibilities that the Bayesian approach affords. Ideal for teaching and self study, this book demonstrates how to do Bayesian modeling. Short, to-the-point chapters offer examples, exercises, and computer code (using WinBUGS or JAGS, and supported by Matlab and R), with additional support available online. No advance knowledge of statistics is required and, from the very start, readers are encouraged to apply and adjust Bayesian analyses by themselves. The book contains a series of chapters on parameter estimation and model selection, followed by detailed case studies from cognitive science. After working through this book, readers should be able to build their own Bayesian models, apply the models to their own data, and draw their own conclusions. Ideal for teaching and self study, this practical book demonstrates how cognitive scientists can conduct Bayesian analyses for many real-life modeling problems. Supported by examples, exercises, computer code and additional resources available online, readers will learn to take full advantage of the exciting possibilities that the Bayesian approach affords. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

  • Language: English

    Published by Cambridge University Press, 2014

    1107603579 / 9781107603578

    • Softcover
    • Print on Demand

    Seller: moluna, Greven, Germanymoluna

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    Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Ideal for teaching and self study, this practical book demonstrates how cognitive scientists can conduct Bayesian analyses for many real-life modeling problems. Supported by examples, exercises, computer code and additional resources available online, reade.