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  2. Sandsynlighedsregning og statistik
  3. Bayesiansk statistik

The Statistical Analysis of Small Data Sets

Af: Graeme D. Ruxton, Markus Neuhauser Engelsk Paperback

The Statistical Analysis of Small Data Sets

Af: Graeme D. Ruxton, Markus Neuhauser Engelsk Paperback
Tjek vores konkurrenters priser
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.
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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.
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Produktdetaljer
Sprog: Engelsk
Sider: 160
ISBN-13: 9780198872986
Indbinding: Paperback
Udgave:
ISBN-10: 0198872984
Kategori: Bayesiansk statistik
Udg. Dato: 30 aug 2024
Længde: 11mm
Bredde: 156mm
Højde: 233mm
Forlag: Oxford University Press
Oplagsdato: 30 aug 2024
Forfatter(e): Graeme D. Ruxton, Markus Neuhauser
Forfatter(e) Graeme D. Ruxton, Markus Neuhauser

Kategori Bayesiansk statistik

ISBN-13 9780198872986

Sprog Engelsk

Indbinding Paperback

Sider 160

Udgave

Længde 11mm

Bredde 156mm

Højde 233mm

Udg. Dato 30 aug 2024

Oplagsdato 30 aug 2024

Forlag Oxford University Press

Kategori sammenhænge