Here is a short list of visualizations and tools I found useful in teaching statistics to undergraduates. Most links point to a complete range of visualizations. They've been always helpful to explain statistical concepts, especially in live-demonstrations, and I found them to be of very high quality. I've included some of them into the module where I saw fit, but I wanted to note them down here are especially helpful for live demonstrations and in slides. I bet others also have resources with helpful visualizations like this - how about sharing them in this issue as well?

• Probability, Distributions, Effect sizes, Inference, Regression: https://seeing-theory.brown.edu/
• P-hacking, power, p-values, distributions, error types, Bayes factors, ...: https://shinyapps.org/
• Specifically on sampling: https://ismay.shinyapps.io/okcupidheights/
• distribution (also p-value distribution), testing, effect sizes, ...: https://rpsychologist.com/viz

http://www.nature.com/collections/qghhqm

Might be good to include a brief lesson on how to report results to facilitate reproducibility; e.g., in terms of reporting effect sizes, etc. There seems to be a formula for doing this, but also formulae for doing it wrong (which many people still use)

This page which is also here as source contains a broken link to http://faculty.washington.edu/kenrice/BayesIntroClassEpi515.pdf. The author of the original PDF has a more recent course that seems to be a good replacement.

looking at http://www.reproducibleimaging.org/module-stats/02-Effect-size/ -- first question is within properly formatted box... the rest are boring gray boxes.

seems yet to be done

first url link leads just to https://www.hackerrank.com/dashboard which is not clear how it is "a great link for teaching"... anyways -- content seems need to be worked on

on slide 17/27 you cite "Carp 2012". I find multiple "Carp 2012". Can you provide a more complete reference? Thanks.