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 ...

This summer, the Psi Chi Journal of Psychology Research published  Rouse, Russel, and Campbell's Beyond the textbook: Psi Chi Journal articles in introductory psychology courses. It is a curated list of paywall-free Psi Chi articles, mostly with student co-authors, that are peer-reviewed and of an appropriate writing level and length to use in an Introduction to Psychology course. The authors provide the following information for each of the articles: In addition to being appropriate for Into Psych, these articles are also perfect for Intro Stats. In my classes, I emphasize the ability to read and write simple result sections. One way I would review this skill is by showing my students Results sections from published research and asking them to identify the test statistics, effect size, and other relevant information. This selection of articles features clear and concise results sections for t -tests, ANOVA, factorial ANOVA, regression, and correlation. I created a spreadsheet...

So, the Journal of the American Medical Academy publishes v isual abstracts  for some of its research articles. I've written about them before (in particular, this example that illustrates an ANOVA ). These abstracts succinctly summarize the research. They feel like an infographic but contain all of the main sections of a research paper. They are great. They quickly relate the most essential parts of a research study and have a home in Intro Stats.  I love them in Psych Stats and use them for several reasons. 1. Using medical examples reminds Psych Stats students that Psych Stats is really Stats Stats, and stats are used everywhere. 2. These are simplified real-world examples. JAMA creates these to help highlight essential facts for journalists and the public, so Intro Stats students are more than ready to take these on. 3. I like to use these as a quick review of some of the inferential tests we teach in stats. This is no guarantee that basic stats were used in the project, b...

Factorial ANOVA example ahead! With a lovely interaction. And I have a year old and a 4.5 year old and they are sickly daycare kids, so this example really spoke to me. NPR did a story about a recent publication that studied how we administer medicine to our kids and provides evidence for a few things I've suspected: Measuring cups for kid medicine are a disaster AND syringes allow for more accurate dosing, especially if the dose is small. The researchers wanted to know if parents properly dosed liquid medicine for their kids. The researchers used a 3 (dosage, 2.5, 5.0, 7.5 ml) x 3 (modality: small syringe, big syringe, medicine cup) design. They didn't use factorial ANOVA in their analysis, this example can still be used to conceptually explain factorial ANOVA. Their findings: How to use in class: -An easy-to-follow conceptual example of factorial ANOVA (again, they didn't use that analysis in the original paper, but the table above illustrates factorial ANO...