ENSP305 -- Applied Quantitative Methods in Environmental Science and Policy. Prerequisite: One semester each of calculus and statistics. Credit only granted for: ENSP305 or AREC382.
This course is intended for students interested in pursuing career or graduate research opportunities that will include management of environmental databases, detailed analysis of environmental data, and/or application of predictive environmental models. The course is also designed to be accessible to non-science majors interested in practical quantitative analysis of environmental data as a component of environmental policy development and environmental law. Students will learn necessary skills to manage and analyze environmental data through hands-on training in commonly used software and a series of topical case studies. Data analysis and data management will be taught using publically available real-world environmental data sets, including examples from marine and coastal settings, wildlife, soils and contamination, environmental geology, and others.
Applied topics covered in this course will supplement previous coursework in introductory statistics and mathematics. Credit will only be given for ENSP 305 or AREC 382.
By the end of the course, students will be able to:
· Perform advanced quantitative data analysis using Microsoft Excel, including simple and complex functions, array functions, data filtering, application of lookup tables, importing and exporting data from/to specified file formats and illustrate complex data sets in charts and tables
· Perform statistical analysis using Microsoft Excel and the U.S. EPA software package ProUCL. Statistical analyses will include regression analysis, trend analysis, frequency distributions, correlation analysis, measures of central tendency and variability, and hypothesis testing
· Develop, manage and query environmental databases using Microsoft Access
· Identify common sources of publically available environmental data, including from the USGS, NOAA, U.S. EPA, and DOE
· Understand basic concepts in environmental modeling, including model parameterization, calibration and sensitivity analysis. Develop and apply environmental models using the Microsoft Excel Solver package and selected U.S.EPA-developed environmental modeling platforms.
· Prepare a professional-level environmental report including reporting of raw environmental data, summary tables, quantitative and statistical analyses, descriptive charts, and supplementary text to describe the data and associated analyses.
Interested students should contact Dr. Greg Schnaar at firstname.lastname@example.org.