Isbn: 9780198872986 - the statistical analysis of small data sets (13 risultati)

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Da: Bay State Book Company, North Smithfield, RI, U.S.A.Bay State Book Company
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Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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Da: INDOO, Avenel, NJ, U.S.A.INDOO
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Da: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US
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Da: PBShop.store UK, Fairford, GLOS, Regno UnitoPBShop.store UK
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Da: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand
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Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
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EUR 55,09
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Paperback. Condizione: Brand New. 192 pages. 6.14x9.21x0.32 inches. In Stock.

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Da: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
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Paperback. Condizione: new. Paperback. We live in the era of big data. However, small data sets are still common for ethical, financial, or practical reasons. Small sample sizes can cause researchers to seek out the most powerful methods to analyse their data, but they may also be wary that some methodologies and assumptions may not be appropriate when samples are small. The book offers advice on the statistical analysis of small data sets for various designs and levels of measurement, helpingresearchers to analyse such data sets, but also to evaluate and interpret others' analyses.The book discusses the potential challenges associated with a small sample, as well as the waysin which these challenges can be mitigated. General topics with strong relevance to small sample sizes such as meta-analysis, sequential and adaptive designs, and multiple testing are introduced. While the focus is on hypothesis tests and confidence intervals, Bayesian analyses are also covered. Code written in the statistical software R is presented to carry out the proposed methods, many of which are not limited to use on small data sets, and the book also discusses approaches to computingthe power or the necessary sample size, respectively. This book offers advice on the statistical analysis of small data sets (which are often used for ethical, financial, or practical reasons) for various designs and levels of measurement, helping researchers to analyse such data sets, but also to evaluate and interpret others' analyses. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

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Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
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EUR 53,32
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Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
Contatta il venditoreVenditore con 5 stelleCondizione: Usato - Come nuovo
EUR 59,46
EUR 17,60 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 4 disponibili
Condizione: As New. Unread book in perfect condition.

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Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
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EUR 80,74
EUR 11,73 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 2 disponibili
Paperback. Condizione: Brand New. 192 pages. 6.14x9.21x0.32 inches. In Stock.

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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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EUR 82,98
EUR 35,00 spedizioneSpedito da Germania a U.S.A.Quantità: 2 disponibili
Taschenbuch. Condizione: Neu. Neuware - We live in the era of big data. However, small data sets are still common for ethical, financial, or practical reasons. Small sample sizes can cause researchers to seek out the most powerful methods to analyse their data, but they may also be wary that some methodologies and assumptions may not be appropriate when samples are small. The book offers advice on the statistical analysis of small data sets for various designs and levels of measurement, helping researchers to analyse such data sets, but also to evaluate and interpret others' analyses. The book discusses the potential challenges associated with a small sample, as well as the ways in which these challenges can be mitigated. General topics with strong relevance to small sample sizes such as meta-analysis, sequential and adaptive designs, and multiple testing are introduced. While the focus is on hypothesis tests and confidence intervals, Bayesian analyses are also covered. Code written in the statistical software R is presented to carry out the proposed methods, many of which are not limited to use on small data sets, and the book also discusses approaches to computing the power or the necessary sample size, respectively.…