Leveraging real world data in an introductory statistics

Leveraging real world data in an introductory statistics course 9: 00 - 9: 30 Jodi Fasteen (Carroll College)

Visualizing Data • Start with a real world data set Pulse. Of. The. Nation. Sept 2017 Data – • Public opinion survey for 1000 adults, randomly sampled. • (Use the tab Tinker. Plots. Version to copy data directly into Tinker. Plots) • What do you wonder? What questions would spark curiosity for your students? • Use Tinker. Plots to sort data and see what you can discover. • What questions would interest your students? • Order and stack data, create plots

What’s in this data set? • Basics: age, gender, race, income, political affiliation And then some other questions: • What would you say is the likelihood that your current job will be entirely performed by robots or computers within the next decade? • If you had to choose: would you rather be smart and sad, or dumb and happy? • True or false: the earth is always farther away from the sun in the winter than in the summer.

What did you wonder about? What did you discover? •

Who What When Where Why Who is our target audience? • Introductory statistics students, as well as data science students. • How do we get students interested in the data? How

Who What When Where Why How What do we mean by real data? • By “Real Data” we mean data that is gathered through statistically appropriate methods, e. g. surveys, polls, scientific experiments, data scraping, random samples from larger existing data sets, etc. • Stepping away from data that is manufactured by the teacher / textbook. • We want students to be asking questions of the data

Who What When Where Why How When do we use real data? • We’ve made an attempt to incorporate real data throughout the term, including student generated data in the first week and growing to larger and more complicated data sets though out the term. • We don’t just save this for that last part of the term. Authentic data can have a motivating impact throughout the term • We revisit data sets repeatedly over the term

Who What When Where Why Where? • Because we want students to work with the data themselves, our stats classes are taught in a computer lab. Our students work with Tinker. Plots and Excel or R during nearly every class period. How

Who What When Where Why? • Promotes student engagement & curiosity • Encourages students to ask their own questions of data • Common danger in teaching: answering questions that no one in the room has asked • Allows practice with “messy data” How

Who What When Where Why How to find data • Online resources • The. Pulseofa. Nation. com • Kaggle. com ex) Video game data, OKCupid, Air. Bn. B, Census data • Open source curriculum • Active. Stats materials • Open. Intro Statistics by Diez, Barr, & Cetinkaya-Rundel • Community resources • Local government agencies ex) Blackfoot River Fish data • Colleagues in other disciplines • Current events – not just at election season How