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Showing posts with the label variable

Assessing an intervention: A quick exercise for your classes, specialized to your own university.

 Here is a quick RM review I created for my Psych Stats students. We were preparing for the first exam, which covered the very basics of research methodology, including IVs and DVs. We also talk about data visualizations and how they can be used to quickly convey information.  California is dealing with an energy crisis and a heatwave. California tried a relatively inexpensive intervention to reduce the likelihood of overwhelming the energy grid: Sending out text messages during extremely high energy usage. See:   https://www.bloomberg.com/news/articles/2022-09-07/a-text-alert-may-have-saved-california-from-power-blackouts And what happened? People reduced their electric usage. Source: https://www.bloomberg.com/news/articles/2022-09-07/a-text-alert-may-have-saved-california-from-power-blackouts For the class review, I asked my students to think of the emergency alerts they receive from their university via our campus safety app. I challenged them to think of a c...

AI and COVID: A quick example of garbage in, garbage out

Sometimes, I post whole class lessons. Sometimes, I post short little example nuggets. Today I share the latter.  This one is a brief, easy-to-understand example of why AI only learns what we teach it and how even a smarty pants computer can get a little confused about correlations and what they mean. A great way to introduce ML, AI, problems with both, and even discuss correlation and predictions and regression. https://twitter.com/hoalycu/status/1507770891786096643...in my head, I imagine that AI was just judging comic-sans font. The text in this tweet was from a MIT Technology Review article by WIll Douglas Heaven: https://www.technologyreview.com/2021/07/30/1030329/machine-learning-ai-failed-covid-hospital-diagnosis-pandemic/ If you want to go deeper with this example, I strongly recommend reading Dr. Cat Hicks's thread about this post:  https://twitter.com/grimalkina/status/1508095358693302275 .

Ways to use funny meme scales in your stats classes

Have you ever heard of the theory that there are multiple people worldwide thinking about the same novel thing at the same time? It is the multiple discovery hypothesis of invention . Like, multiple great minds around the world were working on calculus at the same time. Well, I think a bunch of super-duper psychology professors were all thinking about scale memes and pedagogy at the same time. Clearly, this is just as impressive as calculus. Who were some of these great minds? 1) Dr.  Molly Metz maintains a curated list of hilarious "How you doing?" scales.  2) Dr. Esther Lindenström posted about using these scales as student check-ins. 3) I was working on a blog post about using such scales to teach the basics of variables.  So, I decided to create a post about three ways to use these scales in your stats classes:  1) Teaching the basics of variables. 2) Nominal vs. ordinal scales.  3) Daily check-in with your students.  1. Teach your students the basics...

Hyperbole and a Half's "Boyfriend doesn't have ebola. Probably. "

I've been using this example in class for a few years but never got around to blogging about it until now. It seems that the first chapter of every statistics class provides a boring explanation of what a variable is, and examples of variables, and operationalizing variables, and quantifying the abstract for the purposes of conducting statistical analyses. I try to make that boring topic funnier and applicable to real life via this post entitled "Boyfriend doesn't have ebola. Probably." from Allie Brosh, editor of Hyperbole and a Half . In this posting, she rips apart the good old FACES scale after a trip with her boyfriend to the ER.