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 ...

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 ...