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Course Description

Designed for graduate and advanced undergraduate students who will be analyzing data and want to develop a practical hands-on toolkit. Topics including data collection and management, exploratory data analysis, fitting and checking models, simulation, handling missing data and presentation of results will be developed through a series of case studies based on different types of data requiring a variety of statistical methods. Statistical programming techniques including functions, graphs and tables will be emphasized. Students should have familiarity with basic concepts of statistics through regression. Permission of instructor required.