Titlebook: Laboratory Experiments in Information Retrieval; Sample Sizes, Effect Tetsuya Sakai Textbook 2018 Springer Nature Singapore Pte Ltd. 2018 I

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The Correct Ways to Use Significance Tests,esting (Sect. 5.1). Then it argues the importance of effect sizes, which typically represent the magnitude of the difference between systems (Sect. 5.2), and finally proposes how researchers should present their significance test results in technical papers and reports (Sect. 5.3). Reporting individ

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Topic Set Size Design Using Excel, an overview of five topic set size design methods is provided (Sect. 6.1), followed by details on each method (Sects. 6.2, 6.3, 6.4, 6.5, and 6.6). These methods are based on a desired statistical power (for the paired .-test, the two-sample .-test, and one-way ANOVA) or on a desired cap on the exp

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Power Analysis Using R,e conducted in the future. Here, “better” means “ensuring appropriate statistical power”. First, an overview of the five R scripts is given (Sect. 7.2), followed by a description of each script (Sects. 7.3, 7.4, 7.5, 7.6, and 7.7). The five scripts, which are for paired .-test, two-sample .-test, on

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1871-7500 ison procedures with Excel and R.Introduces tools for designCovering 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

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The Correct Ways to Use Significance Tests,ual results effectively means that the research community as a whole can accumulate reproducible pieces of evidence and draw general conclusions from them; if researchers adhere to bad practices, that would mean a community where very little is learnt from one another.

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978-981-13-4581-4Springer Nature Singapore Pte Ltd. 2018

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