Statistics for Sports and

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. http://www.dropshippers.co.za/

“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,” http://www.dropshippers.co.za/

- Dr Mick Wilkinson, Department of Sport Sciences, Northumbria University http://www.dropshippers.co.za/

"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 http://www.dropshippers.co.za/

“Incredibly easy to read, full of real-life examples, and very much appropriate for Sports Science students.” http://www.dropshippers.co.za/

- Dr Kate Reed, Department of Biological Sciences, University of Essex http://www.dropshippers.co.za/

About the Author

John Newell is a Senior Lecturer in Biostatistics at the Clinical Research Facility, National University of Ireland, Galway. http://www.dropshippers.co.za/

Tom Aitchison is a retired Senior Lecturer in Statistics at the University of Glasgow. http://www.dropshippers.co.za/

Stanley Grant is a retired Senior Lecturer at the Institute of Biomedical and Life Sciences, University of Glasgow. http://www.dropshippers.co.za/

Table of Contents

• 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
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