Statistical Analysis in Sport & Exercise Science

Recommended Reading

Altman, D. G., & Bland, J. M. (1995). Statistics notes: Absence of evidence is not evidence of absence. Bmj, 311(7003), 485. https://doi.org/10.1136/bmj.311.7003.485

Atkinson, G., & Nevill, A. M. (1998). Statistical methods for assessing measurement error (reliability) in variables relevant to sports medicine. Sports Medicine, 26(4), 217-238. doi.org/10.2165/00007256-199826040-00002

Bailey, C. (2019). Longitudinal Monitoring of Athletes: Statistical Issues and Best Practices. Journal of Science in Sport and Exercise, 1-11. doi.org/10.1007/s42978-019-00042-4

Conway, B. (2017) Smallest Worthwhile Change - https://www.scienceforsport.com/smallest-worthwhile-change/

Drake, D., Kennedy, R., & Wallace, E. (2018). Familiarization, validity and smallest detectable difference of the isometric squat test in evaluating maximal strength. Journal of sports sciences, 36(18), 2087-2095. doi.org/10.1080/02640414.2018.1436857

Flanagan, E. P. (2013). The effect size statistic—Applications for the strength and conditioning coach. Strength & Conditioning Journal, 35(5), 37-40.

Greenland, S., Senn, S. J., Rothman, K. J., Carlin, J. B., Poole, C., Goodman, S. N., & Altman, D. G. (2016). Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations. European journal of epidemiology, 31(4), 337-350. https://doi.org/10.1007/s10654-016-0149-3

Halsey, L. (2019) The reign of the p-value is over: what alternative analyses could we employ to fill the power vacuum? Biol. Lett. 15: 20190174 https://doi.org/10.1098/rsbl.2019.0174

Kelley, K., & Preacher, K. J. (2012). On effect size. Psychological Methods, 17(2), 137. http://dx.doi.org/10.1037/a0028086

Hanel, P. H., Maio, G. R., & Manstead, A. S. (2018). A new way to look at the data: Similarities between groups of people are large and important. Journal of personality and social psychology. http://dx.doi.org/10.1037/pspi0000154

Nead, K. T., Wehner, M. R., & Mitra, N. (2018). The use of “trend” statements to describe statistically nonsignificant results in the oncology literature. JAMA Oncology, 4(12), 1778-1779. doi:10.1001/jamaoncol.2018.4524

Rafi, Z., & Greenland, S. (2020). Semantic and cognitive tools to aid statistical science: replace confidence and significance by compatibility and surprise. BMC medical research methodology, 20(1), 1-13. https://doi.org/10.1186/s12874-020-01105-9

Sauret, J. (2018) Reliability - https://www.scienceforsport.com/reliability/

Spiegelhalter, D. (2019) The Art of Statistics: Learning from Data. Pelican Books

Stark, P. B., & Saltelli, A. (2018). Cargo‐cult statistics and scientific crisis. Significance, 15(4), 40-43.

Sullivan, G. M., & Feinn, R. (2012). Using effect size—or why the P value is not enough. Journal of graduate medical education, 4(3), 279-282. https://doi.org/10.4300/JGME-D-12-00156.1

Till, K., Morris, R., Emmonds, S., Jones, B., & Cobley, S. (2018). Enhancing the evaluation and interpretation of fitness testing data within youth athletes. Strength & Conditioning Journal, 40(5), 24-33. doi: 10.1519/SSC.0000000000000414

Turner, A. N., Jones, B., Stewart, P., Bishop, C., Parmar, N., Chavda, S., & Read, P. (2019). Total score of athleticism: Holistic athlete profiling to enhance decision-making. Strength & Conditioning Journal, 41(6), 91-101. doi: 10.1519/SSC.0000000000000506

Turner, A., Brazier, J., Bishop, C., Chavda, S., Cree, J., & Read, P. (2015). Data analysis for strength and conditioning coaches: Using excel to analyze reliability, differences, and relationships. Strength & Conditioning Journal, 37(1), 76-83. http://dx.doi.org/10.1519/SSC.0000000000000113

Funder, D. C., & Ozer, D. J. (2019). Evaluating effect size in psychological research: Sense and nonsense. Advances in Methods and Practices in Psychological Science, 2515245919847202. https://doi.org/10.1177/2515245919847202

Wasserstein, R. L., & Lazar, N. A. (2016). The ASA statement on p-values: context, process, and purpose. The American Statistician, 70(2), 129-133. https://doi.org/10.1080/00031305.2016.1154108

Weir, J. P. (2005). Quantifying test-retest reliability using the intraclass correlation coefficient and the SEM. The Journal of Strength & Conditioning Research, 19(1), 231-240. DOI: 10.1519/15184.1

Supplementary Reading

Textbooks

Field, A. (2013). Discovering statistics using IBM SPSS statistics. Sage [google books]

Hastie, T., Tibshirani, R., & Friedman, J. (2009). The elements of statistical learning: data mining, inference, and prediction, New York: Springer. [full text]

James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). An introduction to statistical learning: with applications in R. New York: Springer. [full text]

Further Reading/Resources

Further Resources

Getting Started with SPSS - Free Online OU Course

FutureLearn - Data to Insight: An Introduction to Data Analysis and Visualisation - Free Online Course

Bayesian Statistics (an introduction) - Free Online OU Course

Excel Tricks for Sports - A YouTube Channel - https://www.youtube.com/channel/UCagflprv_C-UPPdzSJ0bMCA

Watch a video

Adam Virgile has a growing collection of videos on the use of MS Excel for Sport & Exercise Science

Anthony Turner has produced some excellent videos to complement some of his publications on the use of statistics in Strength & Conditioning and the full set can be found here. Below are a few choice videos.

Which Stats Test: A Sage ResearchMethods Resource