Statistics for Sports and Exercise Science: A Practical ApproachStatistics 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.
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Contents
Testing hypotheses | 4-5 |
regression | 4-58 |
independent observations | 6-26 |
Modelling categorical data | 6-70 |
Summarising and displaying data | 9-3 |
more | 10 |
Other editions - View all
Statistics for Sports and Exercise Science John Newell,Tom Aitchison,Stanley Grant No preview available - 2010 |
Common terms and phrases
ANOVA Ascent assumption average Balance between-subject factor blood lactate Body Fat Body Mass box plot categorical variable Chapter Climber Type CMJ Height Coef coefficient compared Conclusian Control Coping Assets covariate data file Data Name dependence difference in population evidence example Exercise Regime exercise science explanatory variables Figure fitted Gaelic football given in Box Grip Strength Heart Rate hypothesis test Illustration interaction interval estimate Intervention involving km Running levels Mean StDev median methods Mont Blanc multiple comparisons Name of data Normal distribution null hypothesis observations P-value pairwise Peak Power population mean population proportions pre-study prediction prediction interval random randomised regression model Relative Intensity residuals response variable sample mean Scatter plot significantly simple linear regression slopes soccer players Soda Lime sports and exercise Sprint standard deviation StDev SE Mean Stroke Length Study description t-test Treatment V.O2 max variable of interest within-subject factor zero