After months of hard work, hypothesizing, data collection...then you hold your breath and click "OK" in SPSS... From "I fucking love science" FB page

Here is a publication  from Teaching of Psychology in which I outline not one, not two, not three, but FOUR free/cheap internet based activities to be used in statistics/research methods classes. (If you have access to ToP publications, you can also get it here .)

How to lie with accurate data...note how Fox News used a "creative' graph in order to make an 8.6% unemployment rate look like a 9% unemployment rate. Full story available at Media Matters (which, admittedly, is very left-leaning). From Media Matters

Colorful title aside,  this article  teaches critical thinking when analyzing scientific writing for validity and reliability. Property of io9.com As a Social Psychologist, I'm especially grateful that they covered the "Study of Duh" criticism. It also adresses the difference between bad science and bad journalism and why one needs to see the source material for research before they are in a position to truly evaluate a study.

I use this when introducing the availability heuristic in Intro and Social (good ol' comparison of fatal airline accidents vs. fatal car crashes), but I think it could also be used in a statistics class. For starters, it is a novel way of illustrating data. Second, you could use it to spark a discussion on the importance of data-driven decision making when it comes to public policy/charitable giving. For instance, breast cancer has really good PR, but more women are dying of cardiovascular disease...where should the NSF concentrate its efforts to make the biggest possible impact? Property of Newsweek More of same from Curiosity.com... curiosity.com  https://pbs.twimg.com/media/Bur_W0hCMAAOidE.png

The language blue, so use at your own risk...  but this faux debate is hilarious . I use it in my I/O and statistics classes to illustrate reliability, psychometric concerns related to test takers who are not totally engaged in their task, etc.

A chocolate study seems very appropriate for the day after Easter. Messerli's study found a strong and positive correlation between a nation's per capita chocolate consumption and the number of Nobel prizes won by that nation (see graph below). The research article is a pretty straight forward: The only statistical analysis conducted was a correlation, the journal article is very short, and it used archival data. As such, you can use this example to illustrate correlation and archival data as well as the dread "third variable" problem (by asking students to generate variables that may increase chocolate consumption as well as top-notch research/writing/peace/etc.). Property of Messerli/New England Journal of Medicine