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Lesson plan to teach statistical literacy to elementary school students

Today, I'm taking a break from blogging about college teaching and sharing a mini-lesson I created for elementary school-aged students. I am sharing my activity here because I bet I'm not the only college instructor who has been asked to do community outreach with kids, be it at local STEM festivals, children's museums, or elementary school career exploration days. Feel free to take this idea and run with it. I taught this lesson as part of the Wonder Time series at my local children's museum,  Erie Children's Museum  in Erie, PA. My friend, Claire, is a former stats student and former STEM teacher at my kids' school. She is the current education director at the museum. PS: I love my small town life, and the museum is just a few blocks from my workplace.  A description of the Wonder Time series  My question was, "How do number experts predict the future?" As I put together my lesson, I was inspired by all the different ways instructors are already usin...
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Psychedelics research: A blog post with Beth Morling

 Now and again, I run across a news article or psychological question that is so big that it bleeds out of straight statistics and requires a thorough understanding of the research methodology that guides statistical choices. When that happens, I email my buddy and fellow W.W. Norton author, Beth Morling, and we write a joint blog post. Recently, I emailed her because research on using psychedelics to treat many different mental disorders has been in the news.  President Trump fast-tracked this research,  and the  Journal for the American Medical Association recently published a big meta-analysis  on the topic. Psychedelic research has always interested me because of psychology, but it has always amused me because of how you run a proper double-blind research study if your experimental participants KNOW that they are hallucinating and your control group participants know they are not?  This broader question offers a few great discussion options for you and ...

An expected proportions chi-square, investigating Hollywood ethnic representation vs. USA IRL data

I came across a Reddit post  in which a user did a quick-and-dirty data collection of the ethnicities of the three top-billed actors in each of 100+ million USD-earning movies between 2022 and 2025. They then compared the data to US census data.    Regardless of how Reddit reacted, I saw this and decided that it would make a good example for explaining and performing a chi-square with expected proportions. I'm so fun at parties, guys. While the original sample was 228, I created an imitation sample ( n = 100) with the Hollywood data as the observed data. I used the US census demographic percentages as the expected proportions.  Here is my n = 100 imitation data, in JASP , .TXT , and a text file of the R code generated by JASP. AND PLUS ALSO: The OP in Reddit gave their quick-and-dirty research methodology for collecting data on the ethnic breakdown of the top-billed actors in very successful movies. I think you could challenge your RM students to consider how they ...