57:20
Mastering Meta-Analysis: Key Assumptions and Techniques for High-Quality Outcomes (Nancy Briggs)
01:04:05
The Use of Statistical Software Packages for Research and Teaching- Bradley Wakefield UoW
53:14
Break Free from Independence: Mixed Models for Dependent Data - Gordana Popovic
32:35
It All Depends… Analysing Dependent Observations - Luz Palacios-Derflingher
35:23
Top stats errors to look out for when reading, writing and reviewing papers
53:02
Practical Study Design - Gordana Popovic
48:02
But it isn't significant! What to do with large p-values - Peter Humburg
01:03:24
Five Steps Towards Making Your Analyses Transparent and Reproducible (in R) - Daniel Falster
34:00
What Can a Caterpillar Teach Us About Good Data Visualisation? - Nancy Briggs
41:27
How Can You Get Closer to a RCT When You Can't Do an RCT? - Nick Olsen
41:43
How to avoid p-hacking, HARKing and other statistical sins - Gordana Popovic
54:28
Bootstrapping – How to use your data to get out of a tight spot - Peter Humburg
46:08
Four strategies for dealing with multiple comparisons - Eve Slavich
58:49
A Gentle Introduction to Survival Analysis - Mark Donoghoe
55:47
Survey and Questionnaire Design: Practical advice for researchers - Nancy Briggs
47:14
T-test a special case of regression? Strange but true … - Peter Geelan-Small
01:30:42
Practical Study Design - Gordana Popovic
46:37
It all depends: Interaction terms in regression - Eve Slavich
55:12
A Practical Guide to Meta-Analysis - Zhixin Liu
40:41
Like Cats and Dogs – Why model selection and inference just can’t get along - Peter Humburg
32:26
2020 in graphs - David Warton
35:03
When Your Research Meets a Global Pandemic - Nancy Briggs
46:46
Methods for ranking and quantifying the importance of predictor variables - Eve Slavich
44:43
Visualise high dimensional data with the tourr R package - Gordana Popovic
54:39
Variable selection: too many variables? what next? - Peter Geelan-Small
45:15
Residuals in linear models: More than just what’s left over - Nancy Briggs
50:10
Effect Size – p value is not enough, measure of magnitude matters!- Zhixin Liu
51:08
Mind your Ps: How to use and interpret p-values - Mark Donoghoe
28:36
Now there are two of them! Why you shouldn't dichotomise your variables - Peter Humburg
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