Warning: This research and story include every paint-peeling obscenity in the book. Caution should be used when opening up these links on your work computer and you should really think long an hard before providing these links to your students. However, the research I'm about to describe 1) illustrates z-scores and 2) investigated regional usage of safe-for-the-classroom words like darn, damn, and gosh. So, a linguist, Dr. Jack Grieve  decided to use Twitter data to map out the use of different obscenities by county of the United States. Gawker picked up on this research and created a story about it . How can this be used in a statistics class? In order to quantify greater or lesser use of different obscenities, he created z-scores by county and illustrated the difference via a color-coding system. The more orange, the higher the z-score for a region (thus, greater usage) while blue indicates lesser usage. And, there are three such maps (damn, darn, and gosh) that are safe for us...

While it isn't hypothesis driven research  data, this data was collected to see which states are the sweariest. The data collection itself is interesting and a good, teachable example. First, the article describes previous research that looked at swearing by state (typically, using publicly available data via Twitter or Facebook). Then, they describe the data collection used for the current research: " A new map, though, takes a more complicated approach. Instead of using text, it uses data gathered from ... phone calls. You know how, when you call a customer service rep for your ISP or your bank or what have you, you're informed that your call will be recorded?  Marchex Institute , the data and research arm of the ad firm Marchex,  got ahold of the data that resulted from some recordings , examining more than 600,000 phone calls from the past 12 months—calls placed by consumers to businesses across 30 different industries. It then used call mining technology to isola...