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This interdisciplinary course examines current environmental issues from a macroeconomic perspective, focusing on both the long and short-term economic viability of various proposals to address current environmental challenges. While the discipline of Economics serves as a central focus, the course draws extensively from the perspectives of Sociology, Psychology, Architectural Technology, Hospitality Management, and Engineering/Environmental Control Technology, among others. Traditional goals of economic efficiency will be examined in the context of the need to expand renewable energy sources, green building design and construction, sustainable agriculture and trade, resource allocation and other efforts to combat climate change on a global scale. It focuses on both the long and short-term economic viability of various proposals to address current environmental challenges drawing upon the inherent interdisciplinary connection to these vital economic issues.

This interdisciplinary course examines current environmental issues from a macroeconomic perspective, focusing on both the long and short-term economic viability of various proposals to address current environmental challenges. While the discipline of Economics serves as a central focus, the course draws extensively from the perspectives of Sociology, Psychology, Architectural Technology, Hospitality Management, and Engineering/Environmental Control Technology, among others. Traditional goals of economic efficiency will be examined in the context of the need to expand renewable energy sources, green building design and construction, sustainable agriculture and trade, resource allocation and other efforts to combat climate change on a global scale. It focuses on both the long and short-term economic viability of various proposals to address current environmental challenges drawing upon the inherent interdisciplinary connection to these vital economic issues.

An introductory course in statistics and probability. Topics covered include descriptive statistics, sample spaces and probabilities, discrete probability distributions (Binomial, Hypergeometric), expectation and variance, continuous probability distributions (Normal, Student, Chi-Square), confidence intervals, hypothesis testing, and correlation and linear regression. Spreadsheets are used throughout the semester.

An introductory course in statistics and probability. Topics covered include descriptive statistics, sample spaces and probabilities, discrete probability distributions (Binomial, Hypergeometric), expectation and variance, continuous probability distributions (Normal, Student, Chi-Square), confidence intervals, hypothesis testing, and correlation and linear regression. Spreadsheets are used throughout the semester.

Topics include sample spaces and probabilities, discrete probability distributions (Binomial, Poisson), expectation and variance, continuous probability distributions (Normal, Chi-squared), hypothesis testing, confidence intervals, correlation and regression.

Topics include sample spaces and probabilities, discrete probability distributions (Binomial, Poisson), expectation and variance, continuous probability distributions (Normal, Chi-squared), hypothesis testing, confidence intervals, correlation and regression.