Monday, April 14, 2014

Jon Mueller's Correlation or Causation website

If you teach social psychology, you are probably familiar with Dr. Jon Mueller's Resources for the Teaching of Social Psychology website. You may not be as familiar with Mueller's Correlation or Causation website, which keeps a running list of news stories that summarize research findings and either treat correlation appropriately or suggest/imply/state a causal relationship between correlational variables.

The news stories run the gamut from research about human development to political psychology to research on cognitive ability. When I've used this website in the past, I have allowed my students to pick a story of interest and discuss whether or not the journalist in question implied correlation or causation. Mueller also provides several ideas (both from him and from other professors) on how to use his list of news stories in the classroom.

Monday, April 7, 2014

Kevin Wu's Graph TV

Kevin Wu's Graph TV  uses individual episode ratings (archival data via IMDB) of TV shows, graphs each episode over the course of a series via scatter plot, and generates a regression line.

This demonstrates fun with archival data as well as regression lines and scatter plots. You could also discuss sampling, in that these ratings were provided by IMDB users and, presumably, big fans of the shows (and whether or not this constitutes representative sampling).

The saddest little purple dot is the episode Black Market. Truth!

Monday, March 31, 2014's Standard Normal Distribution Table

Now, I am immediately suspicious of a website entitled "MathIsFun" (I prefer the soft promising teaching aids for statistics that are, say, not awful and boring).

That being said, this app. from may be an alternative to going cross-eyed while reading z-tables in order to better understand the normal distribution.

With this little Flash app., you can select z-scores and immediately view the corresponding portion of the normal curve (either from z = 0 to your z, up to a selected z, or to the right of that z). Above, I've selected z = 1.96, and the outlying 2.5% of the curve is highlighted. 

Now, this wouldn't work for a paper and pencil exam (so you would probably still need to teach students to read the paper table) but I think this is useful in that it allows students to IMMEDIATELY see how z-scores and portions of the of the curve co-vary.