I think that interactive visualizations are better than lengthy, wordy text books when it comes to illustrating statistical principles. One little GIF or interactive website can do a far better job than text or words.
For example: Everything that Kristoffer Magnusson has given us (effect sizes, correlations, etc.).
Here is a new tool for explaining critical regions in Intro Stats.
Matthew McBee created an interactive in shinyapps that shows how critical regions change a) depending on test, b) sample size, change of the shape of the distribution.
With the ol' t-test, you can show how the critical values move around with degrees of freedom
Andplusalso: Matt has also created shiny apps to adjust p-values for multiple comparisons, AND another one for calculating p-values based on a test statistics.
For example: Everything that Kristoffer Magnusson has given us (effect sizes, correlations, etc.).
Here is a new tool for explaining critical regions in Intro Stats.
Matthew McBee created an interactive in shinyapps that shows how critical regions change a) depending on test, b) sample size, change of the shape of the distribution.
With the ol' t-test, you can show how the critical values move around with degrees of freedom
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| What your t-test critical values looks like at df = 3... |
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| ...versus how the those critical values look at df = 80 |
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| Also, you can do the same thing but with F curves. |