Statistics in Sport and Exercise Science assumes no prior knowledge of statistics and uses real-life case studies to introduce the importance of statistics in sport and exercise science. Statistical tests and techniques are described here in a friendly and easy-to-understand manner, giving you the confidence to analyses data and complete your own statistical studies.
"This is the best statistics text I have come across in 7 years of teaching on undergraduate sport degrees. Students have always struggled to see the application of statistics to their degree ... Statistics for Sports and Exercise Science eliminates this problem," - Dr Mick Wilkinson, Department of Sport Sciences, Northumbria University"
Easily the best book in the area, specific material for sport students."- Dr Rodney Kennedy, School of Sport Studies, University of Ulster
"I really like the Newell book and will definitely be recommending it to the students on my two research methods modules... The information in the book is first class." - Dr Adrian W Midgley, Department of Sport, Health and Exercise Science, University of Hull
"Incredibly easy to read, full of real-life examples, and very much appropriate for Sports Science students." - Dr Kate Reed, Department of Biological Sciences, University of Essex
John Newell is a Senior Lecturer in Biostatistics at the Clinical Research Facility, National University of Ireland, Galway.
Tom Aitchison is a retired Senior Lecturer in Statistics at the University of Glasgow.
Stanley Grant is a retired Senior Lecturer at the Institute of Biomedical and Life Sciences, University of Glasgow.
Introduction
Acknowledgements
1 Discovering statistics
2 Designing a study
3 Summarising and displaying data
4 Estimating parameters
5 Testing hypotheses
6 Modelling relationships: regression
7 Investigating between-subject factors: independent observations
8 Modelling categorical data
9 Investigating within-subject factors: dependent observations
10 Investigating studies with between-subject and within-subject factors: more on dependent observations
11 Handling linear mixed-effects models: more on dependent observations
12 Measurement error and method agreement studies
13 Speculating on the sample size required
Appendix: Table of illustrations and exercises
Index