Markus Neuhauser's Books

Nonparametric Statistical Tests

A Computational Approach

By: Markus Neuhauser

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Nonparametric Statistical Tests

A Computational Approach

By: Markus Neuhauser

Nonparametric Statistical Tests: A Computational Approach describes classical nonparametric tests, as well as novel and little-known methods such as the Baumgartner-Weiss-Schindler and the Cucconi tests. The book presents SAS and R programs, allowing readers to carry out the different statistical methods, such as permutation and bootstrap tests. Th

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Page Count

247

Publisher

CRC Press

Published Date

ISBN 10

1439867046

ISBN 13

9781439867044

The Statistical Analysis of Small Data Sets

By: Markus Neuhäuser,Graeme D. Ruxton

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The Statistical Analysis of Small Data Sets

By: Markus Neuhäuser,Graeme D. Ruxton

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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Page Count

161

Publisher

Oxford University Press

Published Date

ISBN 10

0198872992

ISBN 13

9780198872993

Circular Statistics in R

By: Arthur Pewsey,Markus Neuhäuser,Graeme D Ruxton

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Circular Statistics in R

By: Arthur Pewsey,Markus Neuhäuser,Graeme D Ruxton

Circular Statistics in R provides the most comprehensive guide to the analysis of circular data in over a decade. Circular data arise in many scientific contexts whether it be angular directions such as: observed compass directions of departure of radio-collared migratory birds from a release point; bond angles measured in different molecules; wind directions at different times of year at a wind farm; direction of stress-fractures in concrete bridge supports; longitudes of earthquake epicentres or seasonal and daily activity patterns, for example: data on the times of day at which animals are caught in a camera trap, or in 911 calls in New York, or in internet traffic; variation throughout the year in measles incidence, global energy requirements, TV viewing figures or injuries to athletes. The natural way of representing such data graphically is as points located around the circumference of a circle, hence their name. Importantly, circular variables are periodic in nature and the origin, or zero point, such as the beginning of a new year, is defined arbitrarily rather than necessarily emerging naturally from the system. This book will be of value both to those new to circular data analysis as well as those more familiar with the field. For beginners, the authors start by considering the fundamental graphical and numerical summaries used to represent circular data before introducing distributions that might be used to model them. They go on to discuss basic forms of inference such as point and interval estimation, as well as formal significance tests for hypotheses that will often be of scientific interest. When discussing model fitting, the authors advocate reduced reliance on the classical von Mises distribution; showcasing distributions that are capable of modelling features such as asymmetry and varying levels of kurtosis that are often exhibited by circular data. The use of likelihood-based and computer-intensive approaches to inference and modelling are stressed throughout the book. The R programming language is used to implement the methodology, particularly its "circular" package. Also provided are over 150 new functions for techniques not already covered within R. This concise but authoritative guide is accessible to the diverse range of scientists who have circular data to analyse and want to do so as easily and as effectively as possible.

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248

Publisher

OUP Oxford

Published Date

ISBN 10

0191650773

ISBN 13

9780191650772

The Statistical Analysis of Small Data Sets

By: Markus Neuhäuser,Graeme D. Ruxton

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The Statistical Analysis of Small Data Sets

By: Markus Neuhäuser,Graeme D. Ruxton

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.

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Page Count

161

Publisher

Oxford University Press

Published Date

ISBN 10

0198872976

ISBN 13

9780198872979

Nonparametric Statistical Tests

A Computational Approach

By: Markus Neuhauser

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Nonparametric Statistical Tests

A Computational Approach

By: Markus Neuhauser

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Solve jigsaw puzzle

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Page Count

247

Publisher

CRC Press

Published Date

ISBN 10

1439867046

ISBN 13

9781439867044

Circular Statistics in R

By: Arthur Pewsey,Markus Neuhäuser,Graeme D Ruxton

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Circular Statistics in R

By: Arthur Pewsey,Markus Neuhäuser,Graeme D Ruxton

Average ratings

N/A

Write a review

Solve jigsaw puzzle

Age

Page Count

248

Publisher

OUP Oxford

Published Date

ISBN 10

0191650773

ISBN 13

9780191650772

Book's by Markus Neuhauser

Nonparametric Statistical Tests

Nonparametric Statistical Tests

The Statistical Analysis of Small Data Sets

The Statistical Analysis of Small Data Sets

Circular Statistics in R

Circular Statistics in R

The Statistical Analysis of Small Data Sets

The Statistical Analysis of Small Data Sets

Nonparametric Statistical Tests

Nonparametric Statistical Tests

Circular Statistics in R

Circular Statistics in R

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