Students will reflect on and integrate their learning and experience in the following activities: 1) Update personal e-Portfolio. During the updating of their e-Portfolio students will complete a series of activities in which they: - Reflect on the courses they have taken at UMass. - Identify skills that they have attained through this course work. - Explore careers in Resource Economics and identify the careers that are of interest to them. - Identify the skills needed to succeed in the career paths they have identified. - Produce a professional resume and a sample cover letter.

Economic analysis of the financial resource management for a small business. It examines issues such as financial statements and financial planning, capital budgeting and management, investment, risk, profitability, and forecasting.

Basic concepts in regression analysis and econometric methods. Application of methods to real world data; emphasis on application through use of econometric software and microcomputers. Computer labs required. Students undertake research projects.

Not available at this time

Not available at this time

Not available at this time.

Economics of environmental problems, including air, water, and land pollution. Emphasis on analyzing the individual incentive patterns that lead to pollution, and cost-effective regulatory structures that can reduce it. Includes domestic and international issues. (Gen.Ed. SB)

Economics of environmental problems, including air, water, and land pollution. Emphasis on analyzing the individual incentive patterns that lead to pollution, and cost-effective regulatory structures that can reduce it. Includes domestic and international issues. (Gen.Ed. SB)

Emphasis on understanding and interpreting statistical information, and using it to form sound judgments in business situations. Includes brief review of sampling, sampling distributions, and basic inference for one-sample situations; comparison of two populations, chi-square tests for contingency tables, analysis of variance, simple linear regression, and topics in multiple regression and time series. Statistical software used for computations. A project using regression methods required.