The Statistical Analysis of Small Data Sets (Original PDF)
By Markus Neuhäuser and Graeme D. Ruxton
In an age dominated by big data, small data sets remain a common reality due to ethical, financial, or practical constraints. Analyzing small samples requires researchers to seek the most statistically powerful methods, while also recognizing the limitations and potential pitfalls of certain methodologies when sample sizes are limited.
This book serves as a comprehensive guide for analyzing small data sets across various research designs and measurement levels. It not only provides practical strategies for conducting statistical analysis but also equips researchers with the skills to critically evaluate and interpret studies conducted with small samples.
About the Author
After studying statistics (with biology as minor) at the University of Dortmund, Professor Markus Neuhäuser worked as a biostatistician in the pharmaceutical industryfrom 1996 to 2001. Back in academia, he was Senior Lecturer in the Department of Mathematics and Statistics at the University of Otago, New Zealand from 2002 to 2004 and at the University Hospital Essen, Germany from 2004 to 2006). Since 2006 he has been working as a Professor of Statistics at the RheinAhrCampus in Remagen, Germany.
Professor Graeme Ruxton FRSE is a zoologist known for his research into behavioural ecology and evolutionary ecology. Ruxton received his PhD in Statistics and Modelling Science in 1992 from the University of Strathclyde. His studies focus on the evolutionary pressures on aggregation by animals, and predator-prey aspects of sensory ecology. He researched visual communication in animals at the University of Glasgow, where he was professor of theoretical ecology. In 2013 he became professor at the University of St Andrews, Scotland. Ruxton has published numerous papers on antipredator adaptations, along with contributions to textbooks. In 2012 Ruxton was elected a Fellow of the Royal Society of Edinburgh.
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