I just finished teaching Chapter 3 of my text today.  To introduce the idea of quartiles and boxplots, I used two data sets.  The first is from the PayScale ROI Report.  The data set includes annual return on investment, total four year cost, graduation rate, and other variables for all colleges and universities throughout the country.  The data is available at

http://www.payscale.com/college-roi

I also uploaded the data to StatCrunch.  Search for “PayScale_ROI_2017” under Explore > Data.

I used the ROI data to find quartiles, identify outliers (very interesting), and draw boxplots.  By selecting this data, I was able to discuss one of the many factors a student should consider in selecting a college or university.

The second data set I used was from the data archives in the City of Chicago.  This data set lists every employee in the city, their department, employment status, and annual salary.  I used this data to draw side-by-side boxplots by department.  Again, many outliers that we were able to explore.

https://data.cityofchicago.org/Administration-Finance/Current-Employee-Names-Salaries-and-Position-Title/xzkq-xp2w

In both instances, students appreciated the fact that the data sets were obtained “on the fly”.  They definitely appreciated the “realness” of the data.

I very much encourage you to use these data sets in your classes and and also find other data sets that motivate your students.