You have to walk before you can run, right? The basics we teach in Psych Stats help our students walk, but they are not typical of published psychology research. It is difficult for Psych Stat instructors to find good examples of our analyses in recently published research (for an exception, check out Open Stats Lab ). A recent publication caught my eye because I love sending people mail ( scroll down to find my list of recommended, envelope-friendly surprises ).  Liu, P. J., Rim, S., Min, L., & Min, K. E. (2022). The surprise of reaching out: Appreciated more than we think. Journal of Personality and Social Psychology , No Pagination Specified-No Pagination Specified. https://doi.org/10.1037/pspi0000402 Spoiler alert: People love being surprised by mail. Like, more than the sender thinks the receiver will be surprised. I was delighted to discover that this interesting paper consists of multiple studies that use what we teach in Psych Stats. Check out this article s...

This excellent interactive tool provides good examples  of chi-square thinking and interactions.  For more commentary, this  write-up of Orth's researc h  is an easy read. Also, it is an example that doesn't involve politics or COVID. There is a time and place for both in the statistics classroom, but I've missed good, accessible data that doesn't have ANYTHING to do with divisive issues.  The data is from research that asked people how they watch TV: Streaming services, cable TV, binge-watching, etc. All sorts of information on how we watch TV, and with this easy-to-use website, you can create tables from this data. Tables that help you teach all kinds of ideas. You can turn chi-square goodness of fit for whether or not people binge their TV. Into a chi-square test of independence by investigating binging by age (categorized).  You can also change the data visualization so you can see the data in a very traditional chi-square table You can also use these c...

This article from The Economist, " Data from wearable devices are changing disease surveillance and medical research ," has a home in your stats or RM class. It describes how FitBits and Apple Watches can be used to collect baseline medical data for health research. I like it because it is very accessible but still goes into detail about specific research issues related to this kind of data: -How does one operationalize their outcome variable? Pulse, temperature, etc., as proxies for underlying problems. Changes in heart rates have predicted the onset of COVID and the flu.  -Big samples be good! One of the reasons this data works like it does is because it is harvested from a massive number of people using these devices.  -The article gives examples of well-designed experiments that use wearable technology. However, often with massive data collection via tech, the data drives the hypothesis, not the other way around. In our psychology classes, we discuss NHST and the proper w...

 I already knew that Morton Ann Gernsbacher was a genius ( see her excellent, open stats classes that use spreadsheets ). So you can imagine how pleased I was to meet her at APS2022. While her talk and message were great, I am here to share one of her presentation resources: Photofunia. This website creates images that contain your text and words, and I'm pretty amused. I think this could be a low-key way to draw attention to commonly made mistakes and big take-home messages. They work in a Powerpoint but are more attention-grabbing than just using a larger font size or bolding your text.

TL;DR: This cool, interactive website asks you to participate in a replication. It also explains how a researcher decision on how to define "randomness" may have driven the main effect of the whole study. There is also a scatter plot and a regression line, talk of probability, and replication of a cognitive example. Long Version:  This example is equal parts stats and RM. I imagine that it can be used in several different ways: -Introduce the replication crisis by participating in a wee replication -Introduce a respectful replication based on the interpretation of the outcome variable  -Data visualization and scatterplots -Probability -Aging research Okay, so this interactive story from The Pudding is a deep dive into how one researcher's decision may be responsible for the study's main effect.  Gauvrit et al. (2017 ) argue that younger people generate more random responses to several probability tasks. From this, the authors conclude that human behavioral complexity...

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 .

A bit over a year ago, Susan Nolan asked me to chair the Statistical Literacy, Reasoning, and Thinking, Guidelines 2.0 for the Society for the Teaching of Psychology.  We were asked to explore and provide guidance for a) teaching statistical thinking in intro psychology and b) understanding how statistical thinking is taught across the psychology curriculum. This post will highlight the accomplishments of the first group, which created easy-to-implement teaching exercises that emphasize statistical reasoning skills in Intro Psych. The Guidelines 1.0 group provided lists of topics included in Intro Psych. The Guidelines 2.0 convened and created a series of brief, easy-to-apply exercises that correspond to the core topics typically taught in Intro. The sub-committee chair, Dr. Garth Neufeld, shared his considerable expertise about Intro Psychology to lead the group and center each exercise in American Psychological Association and American Statistical Association guidelines for under...