Basic concepts in econometric methods. Estimation of the general linear model with applications to theoretical economic models. Introduction to problems and methods to solve problems common in economic data. Nonlinear models, binary independent variables and binary dependent variable methods. Application of methods to real world data; emphasis is on application through use of econometric software. Students undertake research projects.

This course satisfies the Junior Year Writing requirement for students in RES-ECON. The emphasis is on developing students' skills in critical thinking, writing, and effective communication.

This course satisfies the Junior Year Writing requirement for students in RES-ECON. The emphasis is on developing students' skills in critical thinking, writing, and effective communication.

This course satisfies the Junior Year Writing requirement for students in RES-ECON. The emphasis is on developing students' skills in critical thinking, writing, and effective communication.

This is a stand-alone independent study designed by the student and faculty sponsor that involves frequent interaction between instructor and student. Qualitative and quantitative enrichment must be evident on the proposed contract before consent is given to undertake the study.

Economic analysis of environmental problems focusing on air, water, and land pollution. Emphasis is on analyzing the individual incentives that lead to environmental degradation, the valuation of environmental quality, and the design and evaluation of regulations that seek to improve environmental quality. Includes the economic analysis of global climate change. (Gen.Ed. SB)

This course covers methods of sample-based estimation and inference. Topics include hypothesis testing for two populations, analysis of variance for comparing three or more populations, simple linear regression, topics in multiple regression, and univariate time-series techniques (if time permits) such as moving averages and exponential smoothing. Statistical software is used for advanced computations. Basic algebra required.

This course covers methods of sample-based estimation and inference. Topics include hypothesis testing for two populations, analysis of variance for comparing three or more populations, simple linear regression, topics in multiple regression, and univariate time-series techniques (if time permits) such as moving averages and exponential smoothing. Statistical software is used for advanced computations. Basic algebra required.

This course covers methods of sample-based estimation and inference. Topics include hypothesis testing for two populations, analysis of variance for comparing three or more populations, simple linear regression, topics in multiple regression, and univariate time-series techniques (if time permits) such as moving averages and exponential smoothing. Statistical software is used for advanced computations. Basic algebra required.