This is a nice, concise hand out from APA that touches on the main points for evaluating research. In particular, research that has been distilled by science reporters. It may be a bit light for a traditional research methods class, but I think it would be good for the research methods section of most psychology electives, especially if your students working through source materials. The article mostly focuses on evaluating for proper sampling techniques. They also have a good list of questions to ask yourself when evaluating research: This also has an implicit lesson of introducing the APA website to psychology undergraduates and the type of information shared at APA.org. (including, but not limited to, this glossary of psychology terms .)

How much do our personalities change when we're drunk? Not as much as we think. We know this due to the self-sacrificing research participants who went to a lab, filled out some scales, got drunk with their friends. For science! Here is the research, as summarized by the first author .  Here  is the original study. This example admittedly panders to undergraduates. But I also think it is an example that will stick in their heads. It provides good examples of: 1) Self-report vs. other-report personality data in research. -Two weeks prior to the drinking portion, participants completed a Big Five personality scale as if they were drunk. So, there is the self-report of Drunk!Participant. And during the drinking session, participants had their Big Five judged by research assistants coding their interactions with friends, allowing a more object judgment of the Drunk!Participant. The findings: https://www.psychologicalscience.org/news/releases/personality-may-change-whe...

Brenner, writing for Distractify , has compiled a very healthy list of terrible, terrible graphs and charts . How to use in class: 1) Once you know how NOT to do something, you know how to do it. 2) Bonus points for pointing out the flaws in these charts...double bonus points for creating new charts that correct the incorrect charts. A few of my favorites:

I think that language is fascinating. Back when I taught developmental, I always liked to teach how babies learn to talk in sort of the same way all across the world. I like regional difference in American English (for example, swearing and regional colloquialisms ). So, I really like this research that investigates the rise and fall of slang in America. And I think it could be used in a statistics class. How to use in class? 1. Funny list of descriptive statistics. 2. Research methodology for using Google searches to answer a question. A good opening for discussion of archival data, data mining, and creating inclusion criteria for research methodology. 3. Using graphs to illustrate trends across time. This feature is interactive. 4. Further interactive features demonstrating how heat maps can be used to demonstrate state-by-state popularity over time. Here, "dank memes" peaked in April 2016 in Montana. 5. The author eye-balled the data can came up ...

http://gazomg.deviantart.com/art/Star-Trek-Redshirt-6-The-Walking-Dead-483111105 io9 recaps a talk given by mathematician  James Grime . He addressed the long running Star Trek joke that the first people to die are the Red Shirts. Using resources that detail the ins and outs of Star Trek, he determined that: This makes for a good example of absolute vs. relative risk. Sure, more red shirts may die, absolutely, but proportionally? They only make up 10% of the deaths. Also, I think this is a funny example of using archival data in order to understand an actual on-going Star Trek joke. For more math/Star Trek links, go to space.com's treatment of the speech.

Pew Research Center  is an excellent source for data to use in statistics and research methods classes. I have blogged about them before (look  under the Label pew-pew! ) and I'm excited to share that Pew is starting up a series of videos dedicated to research methods. The new series will be called Methods 101 . The first describes sampling techniques in which weighing is used to adjust imperfect samples as to better mimic the underlying population. I like that this is a short video that focuses on one specific aspect of polling. I hope that they continue this trend of creating very specific videos covering specific topics. Looking for more videos? Check out Pew's YouTube Channel . Also, I have a video tag for this blog. 3/25/2018 They have posted their second video, this one on proper wording for research questions as to avoid jargon and bias.

This article, written by Matt Daniels  for The Pudding , allows you to play around with a whole bunch of Spotify user data in order to generate visualizations of song popularity over time. You can generate custom visualizations using the very interactive sections on this website. For instance, there is a special visualization that allows you to finally quantify the Biggie/Tupac Rivalry. So, data and pop culture are my two favorite things. I could play with these different interactive pieces all day long. But there are also some specific ways you could use this in class. 1) Generate unique descriptive data for different musicians and then ask you students to create visualizations using the software of your choosing. Below, I've queried Dixie Chicks play data. Students could enter their own favorite artist. Note: They data only runs through 2005. 2) Sampling errors: Here is a description of the methodology used for this data: Is this representative of all data...