Designed for students in the social science and business related fields of study. Introduction to basic statistical methods used to collect, summarize, and analyze numerical data. Emphasis on application to decision making; examples from the social sciences and business. Topics include: common statistical notation, elementary probability theory, sampling, descriptive statistics, statistical estimation and hypothesis testing. Basic algebra and familiarity with computer and internet necessary. (Gen.Ed. R2)

Economics of environmental quality and natural resource management; theory of externalities, public goods, and resource extraction. Benefit-cost analyses of natural resource use and preservation of unique resources.

Description not available at this time

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 viable methods. Application of methods to real world data; emphasis is on application through use of econometric software. Students undertake research projects.

The purpose of this course is to present intermediate level microeconomic theory. Primarily we will focus on consumer demand theory and economics of production. Both geometric and mathematical approaches will be presented. This course provides the background necessary for more advanced courses in the department.

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 like moving averages and exponential smoothing. Statistical software is used for advanced computations. Basic algebra required.

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 like moving averages and exponential smoothing. Statistical software is used for advanced computations. Basic algebra required.

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 like moving averages and exponential smoothing. Statistical software is used for advanced computations. Basic algebra required.

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 like moving averages and exponential smoothing. Statistical software is used for advanced computations. Basic algebra required.

Not available at this time.