Welcome to a LECTURES ON STATISTICS and WORKSHOP
Progressive Statistics in Sport Science and Medicine with Professor Will Hopkins, Victoria University of Melbourne, Australia; Norwegian Sport University, Oslo, Norway
"Progressive" refers to his practical and novel approaches to data analysis, including estimation and interpretation of the magnitude of effects and their uncertainty, or "life without p values".
I. Lecture Tuesday 27nd November, 2018, 1.00 pm – 2.30 pm (Lecture hall ….)
Introduction to Sport science resources and magnitude-based Inferences
Statistical Analysis and Data Interpretation
Magnitude-based inferences
II. Workshop 28nd November, 2018, 9.00 am – 11.30 am (Lecture hall ….)
Spreadsheets for group comparisons and controlled trials
Parallel groups trial
Post-only crossover
Pre-post crossover
(research resources at the Sportscience site - sportscience.sportsci.org).
Professor Will Hopkins is a professor (Professor of Research Design and Statistics) at the College of Sport & Exercise Science (Victoria University, Melbourne, Australia) and at in the Defense Institute (Norwegian Sport University, Oslo, Norway).
Professor Will Hopkins' scientific interests include research design and analysis, statistics, modeling of training and sport performance, exercise physiology. Professor Hopkins is the author of over 400 original articles, the number of citations is over 30 000, with the value of Hirsh index equal 79.
He is the honorary member of the American College of Sports Medicine (FACSM) and the European College of Sport Science (FECSS). He is also a member of editorial board in Medicine and Science in Sports and Exercise, Sports Medicine, International Journal of Sports Physiology and Performance, Journal of Strength and Conditioning Research, International Journal of Performance Analysis in Sport and in many others scientific journals.
He is also a co-creator of progressive statistics called magnitude-based inference (MBI).
MBI is an approach to making a decision about the true or population value of an effect statistic taking into account the uncertainty in the magnitude of the statistic provided by a sample of the population. As showed it is superior to the traditional approach to inference, null-hypothesis significance testing. More at the Sportscience site (sportscience.sportsci.org)
