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 ...
TL;DR: Birds fly away from men a bit sooner than they fly away from women. Full stop. Here is the original article, and here is a write-up from Nautilus . I love bird research. I'll get into why below. For now, let me show you how to use this example to teach three different lessons in a stats class. 1. Independent t test example with a data set The researchers shared their data. The researchers didn't analyze this data with a t test. But they did share this data visualization that looks a whole lot like one: Damn, I love the new trend of the box/violin/jitter plot. FYI: Researcher gender/the IV is labeled "gender," and how far the birds were before they flew away/the DV is labeled "FID" (flight initiation distance). Also, I love this example because the data violate the assumption of equal variance and provide a case for discussing Welch's test. 2. Conceptual example for Factorial ANOVA This example pairs well with a previous blog post featuring ...