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Sample Proposal: Quantitative Reasoning

College of Liberal Arts: Department of Economics

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ECO 441K Introduction to Economics

Please give a brief description of the course. Include a description of the specific Quantitative Reasoning skills that students will learn and apply within this course.

This is the second course in quantitative methods in the Economics major. (The first is Eco 329, Economic Statistics, which is an upper-division Economics major requirement. Eco 329 with a C is a prerequisite for Eco 441K. Math 408K and Math 408L, as well as Eco 304K and Eco 304K are prerequisites for Eco 329.). This course is a requirement of the Economics major and must be taken in residence. The entire course focuses on high-level quantitative skills. These skills include use of multiple regression and related models; the theoretical foundations for these methods; how to identify assumptions about the data-generating process that are necessary for the methods to be used; and how to develop an estimating equation, interpret the results, and evaluate the statistical significance of the results. The course teaches statistical methods and demonstrates how to apply the methods to data in order to answer empirical questions about economics that are relevant for economic policy and for business (as well as for social policy, charitable activities, non-government organizations, international relations, etc.). See the supporting documents (syllabus and explanations document) for detail.

Courses that carry the Quantitative Reasoning Flag must emphasize how QR skills can be applied in students’ everyday or professional lives. Please describe the kinds of applications the course uses to teach Quantitative Reasoning. Specific examples from assignments or exams are strongly encouraged.

Introduction to Econometrics teaches students multiple regression and related statistical models. These are the statistical methods that economists use most frequently to analyze data (to measure the impacts of policies and to test economic hypotheses). Multiple regression can be used in many business contexts and in policy formulation and policy evaluation.

Courses that carry the Quantitative Reasoning Flag go beyond a superficial application of equations and strive for understanding of the underlying concepts. Please describe how you teach and assess conceptual understanding of Quantitative Reasoning. Specific examples from class, assignments, or exams are strongly encouraged.

Eco 341K carries the Quantitative Reasoning flag. The lecture part of Eco 441K is the same as Eco 341K. See the supporting documents for more detail. In Eco 441K, students will learn how to estimate and interpret multiple regression models. They also learn (through examples, homework assignments, and writing a research paper) how to specify an estimating equation, and how to assess whether assumptions of the statistical model are satisfied in the context or situation that generated the data. The probability theory underlying the statistical models is emphasized in order to give students a way of thinking about assumptions about the data-generating process (as well as providing a basis for further learning about statistical models).

To satisfy the Quantitative Reasoning Flag, at least half of the course grade must be based on the use of quantitative skills. Please describe the course grading scheme in such a way that clearly demonstrates at least half of the grade requires Quantitative Reasoning. Denote which components require Quantitative Reasoning and the total grade percentage these comprise.

  • Each student writes a research paper in which they apply the methods of this course to a question that they have identified and developed. In this paper, the student explains how to use statistical methods to answer the question (methodology, assumptions, and estimating equation), the findings, and the implications of the findings for the question and for policy. The stages of the paper and discussions in groups of the stages of the paper (feedback) count for 35% of the course grade. See the syllabus for more detail.
  • In homework assignments, students apply the methods of this course to data sets and to estimation results covering a range of economic topics. Homework questions require students to interpret estimation results and to evaluate the statistical significance of estimation results. Some homework questions are conceptual and theoretical, but most are applied. Theoretical and conceptual questions develop a students’ understanding of when (under what circumstances) the methods of the course give reliable results; what can go wrong if assumptions are not met; and why the estimation results have the interpretations they do. Therefore, the theoretical and conceptual homework questions also are essential for students to use the methods of this course. Homework counts for 15% of the course grade.
  • A majority of exam questions involve application of the methods of the course by asking students to interpret estimation results and evaluate the statistical significance of estimation results. (An economic setting, questions about it, a description of data, and estimation results are given to the student, and the student is asked to interpret and evaluate the results.) Exams count for 50% of the course grade.