Abstract
Abstract An applied statistics and data-analysis course designed for students of public management and policy analysis, but suitable as an introductory graduate-level applied course in other contexts, is discussed. The course, Quantitative Methods for Public Management (QMPM), is a departure from traditional instruction in statistics. It uses subject-matter hierarchies to schedule the presentation of substantive material, and it integrates exploratory data analysis (EDA) and standard classical techniques. This integration is accomplished by using exploratory methods to clarify and evaluate analyses performed with classical procedures. The course, taught since 1975 at Carnegie-Mellon University's School of Urban and Public Affairs, has been evaluated experimentally through a randomized assignment of students to either a traditional introductory statistics course or QMPM. We concentrate here on the QMPM approach to teaching regression.
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