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Multiverse = multiple correlation and regression examples!

I love InformationIsBeautiful . They created my favorite data visualization of all tim e.  They also created an interactive scatterplot with all sorts of information about Marvel Comic Universe  films. How to use in class: 1. Experiment with the outcome variables you can add to the X and Y axes: Critical response, budget, box office receipts, year of release, etc. There are more than that; you can add them to either the X or Y axes. So, it is one website, but there are many ways to assess the various films. 2. Because of interactive axes, there are various correlation and regression examples. And these visualizations aren't just available as a quick visual example of linear relationships...see item 3... 3. You can ask your students to conduct the actual data analyses you can visualize because  the hecking data is available . 4. The website offers exciting analyses, encouraging your students to think critically about what the data tells them. 5. You could also squeeze Simp...

Using data about antidepressant efficacy to illustrate Cohen's d, demonstrate why you need a control group, talk about interactions.

This example is from The Economist and behind a paywall. However, it is worth using one of your free monthly views to see these visualizations of how much improvement Ps experience. That said, whenever I talk about antidepressants in class, I remind my students MANY TIMES that I'm not that kind of psychologist, and even if I was, I'm not their psychologist. Instead, they should direct any and all medication questions to their own psychologist. This blog post was inspired by " Antidepressants are over-prescribed, but genuinely help some patients " from The Economist, which was in turn inspired by  " Response to acute monotherapy for major depressive disorder in randomized, placebo-controlled trials submitted to the US FDA: individual participant data analysis", by M.B. Stone et al., BMJ, 2022; "Selective publication of antidepressant trials and its influence on apparent efficacy: updated comparisons and meta-analyses of newer versus older trial s", ...

A fast, interactive example for explaining what we mean when we talk about "training" AI/ML

When I teach regression, I touch on AI/Machine Learning. Because it is fancy regression and ties classroom lessons to real life. During discussions about AI/ML, we often talk about "training" computers to look for something by feeding computers data. Which is slightly abstract. And a bit boring, if you are just talking about a ton of spreadsheets. As an alternative to boring, I propose you ask your students to help train Google's computers to recognize doodles . Visit this website, and a prompt flashes on your screen: You draw the prompt (I used my touchscreen), and Google tries to guess what you drew. Here is my half-done wine glass. Google guessed what it was. The website includes additional information on the data that has already been collected. For every one of the doodles above, you can click through and look at all the ones created in response to each prompt. SO MUCH INFORMATION. If you would like, you can also show your students this explainer video.