I taught two sections of Introduction to Statistics at Carleton College. Students learned to collect data;  identify potential sources of bias and design studies to minimize or eliminate bias; differentiate between causation and mere association; visualize data; summarize data; test hypotheses using randomization tests and standard statistical theory (such as analysis of variance); form confidence intervals using bootstrap and t distributions; create, interpret, and test multiple linear regression models; and communicate their results to an audience with limited statistical experience.

They applied their statistical tools through a semester-long group project to compare a quantitative response variable between two groups. In this project, they posed a research question on any topic that interested them;  gathered gather and organized their data; produced numerical summaries and visualizations of their data;  formally tested their research question; and wrote a report to explain and conclude their work.