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Published by H N H International Limited, 2025
ISBN 10: 1032744006 ISBN 13: 9781032744001
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Paperback. Condition: New. Bayesian Statistics: The Basics provides a comprehensive yet accessible introduction to Bayesian statistics, specifically tailored for any researcher with an interest in statistical methods. It covers the theoretical foundations of Bayesian inference, contrasting it with classical statistical methods like null hypothesis significance testing. The book emphasizes key concepts such as prior and posterior distributions, Bayes' theorem, and the Bayes factor, making them understandable even for readers with minimal mathematical backgrounds.Methodologically, the book offers practical, step-by-step guides on how to conduct Bayesian analyses using the free software package JASP. Each chapter focuses on applying Bayesian methods to common research designs with real-world data. Readers will benefit from the clear examples, visualizations, and JASP screenshots that ensure the learning experience is interactive and easy to follow.Full of practical content, the book emphasizes the advantages of Bayesian model comparison over traditional approaches, especially in quantifying evidence for competing hypotheses. Readers will also learn how to perform sensitivity analyses to assess the impact of different prior assumptions on their results.By the end of the book, readers will get both the theoretical understanding and practical skills to implement Bayesian methods in their own research, making it an invaluable resource for both novice and experienced researchers studying Bayesian statistics.
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Paperback. Condition: New. Bayesian Statistics: The Basics provides a comprehensive yet accessible introduction to Bayesian statistics, specifically tailored for any researcher with an interest in statistical methods. It covers the theoretical foundations of Bayesian inference, contrasting it with classical statistical methods like null hypothesis significance testing. The book emphasizes key concepts such as prior and posterior distributions, Bayes' theorem, and the Bayes factor, making them understandable even for readers with minimal mathematical backgrounds.Methodologically, the book offers practical, step-by-step guides on how to conduct Bayesian analyses using the free software package JASP. Each chapter focuses on applying Bayesian methods to common research designs with real-world data. Readers will benefit from the clear examples, visualizations, and JASP screenshots that ensure the learning experience is interactive and easy to follow.Full of practical content, the book emphasizes the advantages of Bayesian model comparison over traditional approaches, especially in quantifying evidence for competing hypotheses. Readers will also learn how to perform sensitivity analyses to assess the impact of different prior assumptions on their results.By the end of the book, readers will get both the theoretical understanding and practical skills to implement Bayesian methods in their own research, making it an invaluable resource for both novice and experienced researchers studying Bayesian statistics.
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Published by Taylor and Francis Ltd, GB, 2025
ISBN 10: 1032744006 ISBN 13: 9781032744001
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Paperback. Condition: New. Bayesian Statistics: The Basics provides a comprehensive yet accessible introduction to Bayesian statistics, specifically tailored for any researcher with an interest in statistical methods. It covers the theoretical foundations of Bayesian inference, contrasting it with classical statistical methods like null hypothesis significance testing. The book emphasizes key concepts such as prior and posterior distributions, Bayes' theorem, and the Bayes factor, making them understandable even for readers with minimal mathematical backgrounds.Methodologically, the book offers practical, step-by-step guides on how to conduct Bayesian analyses using the free software package JASP. Each chapter focuses on applying Bayesian methods to common research designs with real-world data. Readers will benefit from the clear examples, visualizations, and JASP screenshots that ensure the learning experience is interactive and easy to follow.Full of practical content, the book emphasizes the advantages of Bayesian model comparison over traditional approaches, especially in quantifying evidence for competing hypotheses. Readers will also learn how to perform sensitivity analyses to assess the impact of different prior assumptions on their results.By the end of the book, readers will get both the theoretical understanding and practical skills to implement Bayesian methods in their own research, making it an invaluable resource for both novice and experienced researchers studying Bayesian statistics.
Condition: New. Thomas J. Faulkenberry, PhD, is a professor of psychological sciences and associate dean of the College of Graduate Studies at Tarleton State University in Stephenville, TX (USA). A mathematician by training, he teaches courses on statistics and m.
Language: English
Published by Taylor & Francis Ltd, London, 2025
ISBN 10: 1032744006 ISBN 13: 9781032744001
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Paperback. Condition: new. Paperback. Bayesian Statistics: The Basics provides a comprehensive yet accessible introduction to Bayesian statistics, specifically tailored for any researcher with an interest in statistical methods. It covers the theoretical foundations of Bayesian inference, contrasting it with classical statistical methods like null hypothesis significance testing. The book emphasizes key concepts such as prior and posterior distributions, Bayes theorem, and the Bayes factor, making them understandable even for readers with minimal mathematical backgrounds.Methodologically, the book offers practical, step-by-step guides on how to conduct Bayesian analyses using the free software package JASP. Each chapter focuses on applying Bayesian methods to common research designs with real-world data. Readers will benefit from the clear examples, visualizations, and JASP screenshots that ensure the learning experience is interactive and easy to follow.Full of practical content, the book emphasizes the advantages of Bayesian model comparison over traditional approaches, especially in quantifying evidence for competing hypotheses. Readers will also learn how to perform sensitivity analyses to assess the impact of different prior assumptions on their results.By the end of the book, readers will get both the theoretical understanding and practical skills to implement Bayesian methods in their own research, making it an invaluable resource for both novice and experienced researchers studying Bayesian statistics. Bayesian Statistics provides a comprehensive yet accessible introduction to Bayesian statistics, specifically tailored for any researcher with an interest in statistical methods. It covers the theoretical foundations of Bayesian inference, contrasting it with classical statistical methods like null hypothesis significance testing. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Taschenbuch. Condition: Neu. Bayesian Statistics | The Basics | Thomas J. Faulkenberry | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2025 | Routledge | EAN 9781032744001 | Verantwortliche Person für die EU: Taylor & Francis Verlag GmbH, Kaufingerstr. 24, 80331 München, gpsr[at]taylorandfrancis[dot]com | Anbieter: preigu.
Language: English
Published by Taylor and Francis Ltd, GB, 2025
ISBN 10: 1032744006 ISBN 13: 9781032744001
Seller: Rarewaves.com UK, London, United Kingdom
Paperback. Condition: New. Bayesian Statistics: The Basics provides a comprehensive yet accessible introduction to Bayesian statistics, specifically tailored for any researcher with an interest in statistical methods. It covers the theoretical foundations of Bayesian inference, contrasting it with classical statistical methods like null hypothesis significance testing. The book emphasizes key concepts such as prior and posterior distributions, Bayes' theorem, and the Bayes factor, making them understandable even for readers with minimal mathematical backgrounds.Methodologically, the book offers practical, step-by-step guides on how to conduct Bayesian analyses using the free software package JASP. Each chapter focuses on applying Bayesian methods to common research designs with real-world data. Readers will benefit from the clear examples, visualizations, and JASP screenshots that ensure the learning experience is interactive and easy to follow.Full of practical content, the book emphasizes the advantages of Bayesian model comparison over traditional approaches, especially in quantifying evidence for competing hypotheses. Readers will also learn how to perform sensitivity analyses to assess the impact of different prior assumptions on their results.By the end of the book, readers will get both the theoretical understanding and practical skills to implement Bayesian methods in their own research, making it an invaluable resource for both novice and experienced researchers studying Bayesian statistics.
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