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Abstract:
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With a long history that dates back to the early efforts of Deming, Shewhart, and others, statistical quality control and related topics have increasingly been incorporated into introductory and intermediate courses. Unfortunately, companion issues of data quality (e.g., missingness, digit preference) have not received similar attention, particularly with respect to the collection of information in the health sciences. Beginning with a seminal paper by Hotelling and Hotelling (1932), this presentation provides several examples of how some important data quality issues can be introduced in applied statistics courses. Using large files of historical data and other approaches, these examples can both enhance and enliven the educational experiences of students with more "applied" interests. The timely relevance of such issues to recent work in "health disparities" is emphasized.
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