Developing statistical and quantitative literacy allows us to understand the numbers thrown at us on a daily basis, whether they are from the New York Times, the Census Bureau, or a research article. In elementary and secondary school, students develop necessary skills to understand mathematical principles, but in college they learn more about how social and behavioral phenomena are measured and interpreted. One could almost think about it as word problems on steroids (see what I did there?). In other words, there are many ways things can be measured resulting in different answers depending on which combination of variables you choose to analyze.
Teaching with data can be a bit of a challenge depending on the approach. There is nothing wrong with faculty and graduate students using their own datasets that they’ve collected. After all, they understand all the ins and outs of the data, and they know for sure about its quality. However, there are a lot of high quality datasets out there in the world that can be used for teaching. Some data repositories such as ICPSR have created tools to teach with, and there have been collaborative endeavors such as the National Numeracy Network to assist instructors with a quantitative literacy curriculum.
If you’re interested in teaching with data, or would just like to explore some exercises on your own to build your own skills, the Data and Statistics Guide has an entire tab devoted to Teaching with Data.