Da: Universitätsbuchhandlung Herta Hold GmbH, Berlin, Germania
EUR 14,00
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Aggiungi al carrelloIX, 150 p. Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. The Information Retrieval Series, 40. Sprache: Englisch.
Editore: Springer Nature Singapore, Springer Nature Singapore Dez 2018, 2018
ISBN 10: 9811345813 ISBN 13: 9789811345814
Lingua: Inglese
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
EUR 53,50
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Neuware -Covering aspects from principles and limitations of statistical significance tests to topic set size design and power analysis, this book guides readers to statistically well-designed experiments. Although classical statistical significance tests are to some extent useful in information retrieval (IR) evaluation, they can harm research unless they are used appropriately with the right sample sizes and statistical power and unless the test results are reported properly. The first half of the book is mainly targeted at undergraduate students, and the second half is suitable for graduate students and researchers who regularly conduct laboratory experiments in IR, natural language processing, recommendations, and related fields.Chapters 1¿5 review parametric significance tests for comparing system means, namely, t-tests and ANOVAs, and show how easily they can be conducted using Microsoft Excel or R. These chapters also discuss a few multiple comparison procedures for researcherswho are interested in comparing every system pair, including a randomised version of Tukey's Honestly Significant Difference test. The chapters then deal with known limitations of classical significance testing and provide practical guidelines for reporting research results regarding comparison of means.Chapters 6 and 7 discuss statistical power. Chapter 6 introduces topic set size design to enable test collection builders to determine an appropriate number of topics to create. Readers can easily use the author¿s Excel tools for topic set size design based on the paired and two-sample t-tests, one-way ANOVA, and confidence intervals. Chapter 7 describes power-analysis-based methods for determining an appropriate sample size for a new experiment based on a similar experiment done in the past, detailing how to utilize the author¿s R tools for power analysis and how to interpret the results. Case studies from IR for both Excel-based topic set size design and R-basedpower analysis are also provided.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 160 pp. Englisch.
Editore: Springer Nature Singapore, Springer Nature Singapore Okt 2018, 2018
ISBN 10: 9811311986 ISBN 13: 9789811311987
Lingua: Inglese
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
EUR 53,50
Convertire valutaQuantità: 2 disponibili
Aggiungi al carrelloBuch. Condizione: Neu. Neuware -Covering aspects from principles and limitations of statistical significance tests to topic set size design and power analysis, this book guides readers to statistically well-designed experiments. Although classical statistical significance tests are to some extent useful in information retrieval (IR) evaluation, they can harm research unless they are used appropriately with the right sample sizes and statistical power and unless the test results are reported properly. The first half of the book is mainly targeted at undergraduate students, and the second half is suitable for graduate students and researchers who regularly conduct laboratory experiments in IR, natural language processing, recommendations, and related fields.Chapters 1¿5 review parametric significance tests for comparing system means, namely, t-tests and ANOVAs, and show how easily they can be conducted using Microsoft Excel or R. These chapters also discuss a few multiple comparison procedures for researcherswho are interested in comparing every system pair, including a randomised version of Tukey's Honestly Significant Difference test. The chapters then deal with known limitations of classical significance testing and provide practical guidelines for reporting research results regarding comparison of means.Chapters 6 and 7 discuss statistical power. Chapter 6 introduces topic set size design to enable test collection builders to determine an appropriate number of topics to create. Readers can easily use the author¿s Excel tools for topic set size design based on the paired and two-sample t-tests, one-way ANOVA, and confidence intervals. Chapter 7 describes power-analysis-based methods for determining an appropriate sample size for a new experiment based on a similar experiment done in the past, detailing how to utilize the author¿s R tools for power analysis and how to interpret the results. Case studies from IR for both Excel-based topic set size design and R-basedpower analysis are also provided.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 160 pp. Englisch.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 61,70
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Aggiungi al carrelloCondizione: New. In.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 61,70
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Aggiungi al carrelloCondizione: New. In English.
Da: GreatBookPrices, Columbia, MD, U.S.A.
EUR 54,49
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Editore: Springer Nature Singapore, Springer Nature Singapore, 2018
ISBN 10: 9811345813 ISBN 13: 9789811345814
Lingua: Inglese
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 56,99
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Covering aspects from principles and limitations of statistical significance tests to topic set size design and power analysis, this book guides readers to statistically well-designed experiments. Although classical statistical significance tests are to some extent useful in information retrieval (IR) evaluation, they can harm research unless they are used appropriately with the right sample sizes and statistical power and unless the test results are reported properly. The first half of the book is mainly targeted at undergraduate students, and the second half is suitable for graduate students and researchers who regularly conduct laboratory experiments in IR, natural language processing, recommendations, and related fields.Chapters 1-5 review parametric significance tests for comparing system means, namely, t-tests and ANOVAs, and show how easily they can be conducted using Microsoft Excel or R. These chapters also discuss a few multiple comparison procedures for researcherswho are interested in comparing every system pair, including a randomised version of Tukey's Honestly Significant Difference test. The chapters then deal with known limitations of classical significance testing and provide practical guidelines for reporting research results regarding comparison of means. Chapters 6 and 7 discuss statistical power. Chapter 6 introduces topic set size design to enable test collection builders to determine an appropriate number of topics to create. Readers can easily use the author's Excel tools for topic set size design based on the paired and two-samplet-tests, one-way ANOVA, and confidence intervals. Chapter 7 describes power-analysis-based methods for determining an appropriate sample size for a new experiment based on a similar experiment done in the past, detailing how to utilize the author's R tools for power analysis and how to interpret the results. Case studies from IR for both Excel-based topic set size design and R-basedpower analysis are also provided.
Editore: Springer Nature Singapore, Springer Nature Singapore, 2018
ISBN 10: 9811311986 ISBN 13: 9789811311987
Lingua: Inglese
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 56,99
Convertire valutaQuantità: 1 disponibili
Aggiungi al carrelloBuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Covering aspects from principles and limitations of statistical significance tests to topic set size design and power analysis, this book guides readers to statistically well-designed experiments. Although classical statistical significance tests are to some extent useful in information retrieval (IR) evaluation, they can harm research unless they are used appropriately with the right sample sizes and statistical power and unless the test results are reported properly. The first half of the book is mainly targeted at undergraduate students, and the second half is suitable for graduate students and researchers who regularly conduct laboratory experiments in IR, natural language processing, recommendations, and related fields.Chapters 1-5 review parametric significance tests for comparing system means, namely, t-tests and ANOVAs, and show how easily they can be conducted using Microsoft Excel or R. These chapters also discuss a few multiple comparison procedures for researcherswho are interested in comparing every system pair, including a randomised version of Tukey's Honestly Significant Difference test. The chapters then deal with known limitations of classical significance testing and provide practical guidelines for reporting research results regarding comparison of means. Chapters 6 and 7 discuss statistical power. Chapter 6 introduces topic set size design to enable test collection builders to determine an appropriate number of topics to create. Readers can easily use the author's Excel tools for topic set size design based on the paired and two-samplet-tests, one-way ANOVA, and confidence intervals. Chapter 7 describes power-analysis-based methods for determining an appropriate sample size for a new experiment based on a similar experiment done in the past, detailing how to utilize the author's R tools for power analysis and how to interpret the results. Case studies from IR for both Excel-based topic set size design and R-basedpower analysis are also provided.
Da: California Books, Miami, FL, U.S.A.
EUR 66,23
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Da: Chiron Media, Wallingford, Regno Unito
EUR 54,63
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 61,69
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Da: Books Puddle, New York, NY, U.S.A.
EUR 72,40
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Da: GreatBookPrices, Columbia, MD, U.S.A.
EUR 64,42
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 67,63
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Da: Revaluation Books, Exeter, Regno Unito
EUR 79,44
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Aggiungi al carrelloHardcover. Condizione: Brand New. 162 pages. 9.25x6.10x0.47 inches. In Stock.
Da: Lucky's Textbooks, Dallas, TX, U.S.A.
EUR 52,94
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Da: Lucky's Textbooks, Dallas, TX, U.S.A.
EUR 53,29
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Da: Mispah books, Redhill, SURRE, Regno Unito
EUR 108,06
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Aggiungi al carrelloPaperback. Condizione: New. New. book.
Da: moluna, Greven, Germania
EUR 47,25
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Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Discusses the principles and limitations of statistical significance testsProvides hands-on examples of t-tests, ANOVA, and multiple comparison procedures with Excel and RIntroduces tools for designing effective experiments by leveraging to.
Da: moluna, Greven, Germania
EUR 47,25
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Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Discusses the principles and limitations of statistical significance testsProvides hands-on examples of t-tests, ANOVA, and multiple comparison procedures with Excel and RIntroduces tools for designing effective experiments by leveraging to.
Editore: Springer Nature Singapore Okt 2018, 2018
ISBN 10: 9811311986 ISBN 13: 9789811311987
Lingua: Inglese
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 53,50
Convertire valutaQuantità: 2 disponibili
Aggiungi al carrelloBuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Covering aspects from principles and limitations of statistical significance tests to topic set size design and power analysis, this book guides readers to statistically well-designed experiments. Although classical statistical significance tests are to some extent useful in information retrieval (IR) evaluation, they can harm research unless they are used appropriately with the right sample sizes and statistical power and unless the test results are reported properly. The first half of the book is mainly targeted at undergraduate students, and the second half is suitable for graduate students and researchers who regularly conduct laboratory experiments in IR, natural language processing, recommendations, and related fields.Chapters 1-5 review parametric significance tests for comparing system means, namely, t-tests and ANOVAs, and show how easily they can be conducted using Microsoft Excel or R. These chapters also discuss a few multiple comparison procedures for researchers who are interested in comparing every system pair, including a randomised version of Tukey's Honestly Significant Difference test. The chapters then deal with known limitations of classical significance testing and provide practical guidelines for reporting research results regarding comparison of means. Chapters 6 and 7 discuss statistical power. Chapter 6 introduces topic set size design to enable test collection builders to determine an appropriate number of topics to create. Readers can easily use the author's Excel tools for topic set size design based on the paired and two-samplet-tests, one-way ANOVA, and confidence intervals. Chapter 7 describes power-analysis-based methods for determining an appropriate sample size for a new experiment based on a similar experiment done in the past, detailing how to utilize the author's R tools for power analysis and how to interpret the results. Case studies from IR for both Excel-based topic set size design and R-based power analysis are also provided. 160 pp. Englisch.
Editore: Springer Nature Singapore Dez 2018, 2018
ISBN 10: 9811345813 ISBN 13: 9789811345814
Lingua: Inglese
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 53,50
Convertire valutaQuantità: 2 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Covering aspects from principles and limitations of statistical significance tests to topic set size design and power analysis, this book guides readers to statistically well-designed experiments. Although classical statistical significance tests are to some extent useful in information retrieval (IR) evaluation, they can harm research unless they are used appropriately with the right sample sizes and statistical power and unless the test results are reported properly. The first half of the book is mainly targeted at undergraduate students, and the second half is suitable for graduate students and researchers who regularly conduct laboratory experiments in IR, natural language processing, recommendations, and related fields.Chapters 1-5 review parametric significance tests for comparing system means, namely, t-tests and ANOVAs, and show how easily they can be conducted using Microsoft Excel or R. These chapters also discuss a few multiple comparison procedures for researchers who are interested in comparing every system pair, including a randomised version of Tukey's Honestly Significant Difference test. The chapters then deal with known limitations of classical significance testing and provide practical guidelines for reporting research results regarding comparison of means. Chapters 6 and 7 discuss statistical power. Chapter 6 introduces topic set size design to enable test collection builders to determine an appropriate number of topics to create. Readers can easily use the author's Excel tools for topic set size design based on the paired and two-samplet-tests, one-way ANOVA, and confidence intervals. Chapter 7 describes power-analysis-based methods for determining an appropriate sample size for a new experiment based on a similar experiment done in the past, detailing how to utilize the author's R tools for power analysis and how to interpret the results. Case studies from IR for both Excel-based topic set size design and R-based power analysis are also provided. 160 pp. Englisch.
Da: Majestic Books, Hounslow, Regno Unito
EUR 72,80
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Aggiungi al carrelloCondizione: New. Print on Demand pp. 150.
Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 76,42
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Aggiungi al carrelloCondizione: New. PRINT ON DEMAND pp. 150.