Peter O'Donoghue

Statistics for Sport and Exercise Studies (eBook, ePUB)

An Introduction

• Format: ePub

Produktbeschreibung

Statistics for Sport and Exercise Studies guides the student through the full research process, from selecting the most appropriate statistical procedure, to analysing data, to the presentation of results, illustrating every key step in the process with clear examples, case-studies and data taken from real sport and exercise settings.

Every chapter includes a range of features designed to help the student grasp the underlying concepts and relate each statistical procedure to their own research project, including definitions of key terms, practical exercises, worked examples and clear summaries. The book also offers an in-depth and practical guide to using SPSS in sport and exercise research, the most commonly used data analysis software in sport and exercise departments. In addition, a companion website includes more than 100 downloadable data sets and work sheets for use in or out of the classroom, full solutions to exercises contained in the book, plus over 1,300 PowerPoint slides for use by tutors and lecturers.

Statistics for Sport and Exercise Studies is a complete, user-friendly introduction to the use of statistical tests, techniques and procedures in sport, exercise and related subjects.

Visit the companion website at: www.routledge.com/cw/odonoghue

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Produktdetails

• Verlag: Taylor & Francis eBooks
• Seitenzahl: 416
• Erscheinungstermin: 19. Juni 2013
• Englisch
• ISBN-13: 9781136479274
• Artikelnr.: 38273420

Autorenporträt

Peter O'Donoghue is Reader and Discipline Director for Performance Analysis in the Cardiff School of Sport, UWIC, UK. Peter started his career as a computer scientist before moving into sport and exercise science in 1997. Since then he has been active in the performance analysis of sport and is Chair of the International Society of Performance Analysis of Sport.

Inhaltsangabe

1. Data, Information and Statistics 2. Using this book 3. Descriptive Statistics 4. Standardized scores 5. Probability 6. Data distributions 7. Hypothesis testing 8. Correlation 9. Linear Regression 10. t Tests 11. Analysis of Variances 12. Factorial ANOVA 13. Multivariate ANOVA 14. Nonparametric tests 15. Chi Square 16. Statistical Classification 17. Cluster Analysis 18. Data Reduction using Principal Components Analysis 19. Reliability 20. Statistical Power