Progressive
Statistics at Sportscience
Prof.
Will Hopkins of AUT University in Auckland NZ will present this two-day series
of lectures and workshop sessions using the research resources at the Sportscience site. "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".
To open Sportscience (sportsci.org) at the homepage in a new tab, click here.
The links
below will then open within the main frame of this page.
General references:
Understanding stats via simulations
Day 1
09:30-10:40
Introduction to Sportscience resources and magnitude-based Inferences
Mechanistic vs clinical inferences
10:40-11:00
Morning tea
11:00-12:30
Magnitudes for differences, changes and correlations
Linear models and
effect magnitudes
Repeated measures & random effects
12:30-13:30
Lunch
13:30-14:40
Workshop: spreadsheets for inferences
Confidence limits & clinical chances · article
Combine/compare effects · article
14:40-15:00
Afternoon tea
15:00-16:00
Workshop: spreadsheets for group comparisons and controlled trials
Compare two group means · article
Pre-post parallel groups trial · article
Article
on choosing the most appropriate controlled trial: Controlled-trials decision tree
16:00-17:00
Consulting with individuals
Day 2
09:30-10:40
Magnitudes for proportions and counts
Linear models and
effect magnitudes (continued)
10:40-11:00
Morning tea
11:00-12:30
Measurement issues: validity, reliability, sample-size estimation
A Socratic dialogue on comparison of measures
12:30-13:30
Lunch
13:30-14:40
Workshop: spreadsheets for reliability, validity and sample-size estimation
Reliability · article
(in A New View of Statistics)
Validity · article
(in A New View of Statistics)
Sample-size estimation · article
14:40-15:00
Afternoon tea
15:00-16:00
Workshop: using SPSS
16:00-17:00
Consulting with individuals