In the last decade, a sea change has occurred in the organization of introductory statistics courses. The mantra of "more data, less lecture" is widely repeated while active learning opportunities receive increasing focus. At Smith College, a small liberal arts college, a number of introductory statistics courses are offered, with varying mathematical prerequisites. Stata is used as the computing environment for many of these courses. In all courses, students engage in the analysis of real-world example datasets, often taught in the form of mini case studies (using a set of lab materials developed at UCLA). For the more mathematically savvy students, introductory statistics concepts are introduced through simulation and other activities. While Stata serves as an easy to use environment for statistical analysis, there are areas where additional functionality would improve its use as a testbed for statistical investigation. In this talk, I will review the use of Stata for both of these purposes, and detail areas of strengths and potential improvements.
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