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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Laboratory Experiments in Information Retrieval: Sample Sizes, Effect Sizes, and Statistical Power

Laboratory Experiments in Information Retrieval: Sample Sizes, Effect Sizes, and Statistical Power

Sakai, Tetsuya

Hardcover

Series: Information Retrieval, Book 40

Probability & StatisticsSystem Administration

ISBN10: 9811311986
ISBN13: 9789811311987
Publisher: Springer Nature
Published: Oct 4 2018
Pages: 150
Weight: 0.89
Height: 0.44 Width: 6.14 Depth: 9.21
Language: English
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.

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