In this talk I cover eight evidence-based principles for improving your data visualisations. Slidedeck available here: https://osf.io/nsbpx/ Figure examples are from this book: https://clauswilke.com/dataviz/index....
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What are preprints?
Making null effects informative using Bayes factors and equivalence tests
How to perform a mean difference meta-analysis using JAMOVI
Improving intranasal oxytocin research by advancing methods, theory, and reproducibility
How to calculate statistical power for studies included in a meta-analysis
How preprints can benefit both science and your career
How open science can boost your career
Increasing the credibility of meta-analysis
How to calculate the statistical power of studies included in a meta-analysis using R
Applying open science practices to clinical research
Exploring the 'patchwork' package for plot composition in #Rstats
How to perform a meta-analysis in R
Robust t-tests in Jamovi and R
Exploring and visualising correlations in R
How to perform a Bayesian meta-analysis in R
Rethinking oxytocin's role in our thoughts, feelings, and behaviours
Testing and adjusting for publication bias in meta-analysis
How to perform a power analysis
How to perform a transparent meta-analysis
Five things that every researcher should know about open science
Improving your data visualizations
Improving the credibility of meta-analysis
How to effortlessly calculate the statistical power of studies included in a meta-analysis