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Effect Sizes for Research, Grissom, Robert J.


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Цена: 7348.00р.
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Автор: Grissom, Robert J.
Название:  Effect Sizes for Research
ISBN: 9780415877695
Издательство: Taylor&Francis
Классификация:

ISBN-10: 0415877695
Обложка/Формат: Paperback
Страницы: 434
Вес: 0.66 кг.
Дата издания: 15.11.2011
Язык: English
Издание: 2 ed
Размер: 230 x 156 x 24
Читательская аудитория: Postgraduate, research & scholarly
Подзаголовок: Univariate and multivariate applications, second edition
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Поставляется из: Европейский союз


The Effect: An Introduction to Research Design and Causality

Автор: Huntington-Klein Nick
Название: The Effect: An Introduction to Research Design and Causality
ISBN: 1032127457 ISBN-13(EAN): 9781032127453
Издательство: Taylor&Francis
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Цена: 13014.00 р.
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Описание: The Effect: An Introduction to Research Design and Causality is about research design, specifically concerning research that uses observational data to make a causal inference. It is separated into two halves, each with different approaches to that subject.

The Effect: An Introduction to Research Design and Causality

Автор: Huntington-Klein Nick
Название: The Effect: An Introduction to Research Design and Causality
ISBN: 1032125780 ISBN-13(EAN): 9781032125787
Издательство: Taylor&Francis
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Цена: 4898.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: The Effect: An Introduction to Research Design and Causality is about research design, specifically concerning research that uses observational data to make a causal inference. It is separated into two halves, each with different approaches to that subject.

Confidence Intervals for Proportions and Related Measures of Effect Size

Автор: Newcombe Robert Gordon
Название: Confidence Intervals for Proportions and Related Measures of Effect Size
ISBN: 0367576708 ISBN-13(EAN): 9780367576707
Издательство: Taylor&Francis
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Цена: 7348.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book illustrates the use of effect size measures and corresponding confidence intervals as more informative alternatives to the most basic and widely used significance tests. It provides you with a deep understanding of what happens when these statistical methods are applied in situations far removed from the familiar Gaussian case. Requiri

Sample Sizes for Clinical Trials

Автор: Julious, Steven A.
Название: Sample Sizes for Clinical Trials
ISBN: 1138587893 ISBN-13(EAN): 9781138587892
Издательство: Taylor&Francis
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Цена: 15004.00 р.
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Confidence Intervals for Proportions and Related Measures of Effect Size

Автор: Newcombe, Robert Gordon
Название: Confidence Intervals for Proportions and Related Measures of Effect Size
ISBN: 1439812780 ISBN-13(EAN): 9781439812785
Издательство: Taylor&Francis
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Цена: 17609.00 р.
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Understanding The New Statistics

Автор: Cumming, Geoff
Название: Understanding The New Statistics
ISBN: 0415879671 ISBN-13(EAN): 9780415879675
Издательство: Taylor&Francis
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Цена: 22968.00 р.
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Applied Power Analysis for the Behavioral Sciences

Автор: Aberson
Название: Applied Power Analysis for the Behavioral Sciences
ISBN: 1138044563 ISBN-13(EAN): 9781138044562
Издательство: Taylor&Francis
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Цена: 22202.00 р.
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Описание: Applied Power Analysis for the Behavioral Sciences is a practical guide to conducting statistical power analyses for students and researchers (including those with limited quantitative backgrounds) in psychology and related fields.

Applied Power Analysis for the Behavioral Sciences

Автор: Aberson
Название: Applied Power Analysis for the Behavioral Sciences
ISBN: 1138044598 ISBN-13(EAN): 9781138044593
Издательство: Taylor&Francis
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Цена: 7654.00 р.
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Описание: Applied Power Analysis for the Behavioral Sciences is a practical guide to conducting statistical power analyses for students and researchers (including those with limited quantitative backgrounds) in psychology and related fields.

Laboratory Experiments in Information Retrieval

Автор: Tetsuya Sakai
Название: Laboratory Experiments in Information Retrieval
ISBN: 9811345813 ISBN-13(EAN): 9789811345814
Издательство: Springer
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Цена: 6988.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: 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-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-based power analysis are also provided.

Laboratory experiments in information retrieval

Автор: Sakai, Tetsuya
Название: Laboratory experiments in information retrieval
ISBN: 9811311986 ISBN-13(EAN): 9789811311987
Издательство: Springer
Рейтинг:
Цена: 6988.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: 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-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-based power analysis are also provided.


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