MATHEMATICS FOR AGRICULTURAL AND APPLIED ECONOMICS
The fundamental mathematics and statistics necessary for the study of quantitative methods in agricultural and applied economics (AAE). Topics include the mathematics of optimization and its role in basic welfare theory and consumer demand; linear and matrix algebra and their application in both modeling consumer behavior and the statistical analysis of models; and the fundamentals of statistical analysis relevant to econometric analysis, including probability theory, sampling distributions and statistical inference.
Topics
- the mathematics of optimization and its role in basic welfare theory and consumer demand
- linear and matrix algebra and their application in both modeling consumer behavior and the statistical analysis of models
- and the fundamentals of statistical analysis relevant to econometric analysis
- including probability theory
- sampling distributions and statistical inference
Topics explicitly listed in official catalogue description
Prerequisites & course information
Requisites: ( ECON 101 , 111 , A A E 101 , or 215 prior to Fall 2024) and ( MATH 211 , 217, or 221 ) or graduate/professional standing Course Designation: Core GenEd - Mathematics & Quantitative Reasoning Repeatable for Credit: No Last Taught: Summer 2024 Learning Outcomes: 1. Solve a constrained optimization problem by applying calculus rules. Audience: Undergraduate 2. Create and interpret basic data visualizations. Audience: Undergraduate 3. Articulate the law of large numbers as it pertains to empirical economic analysis. Audience: Undergraduate 4. Determine statistical significance of parameter estimates & interpret the results. Audience: Undergraduate 5. Use R for basic calculations and simulations. Audience: Undergraduate 6. Explain statistical concepts to a general audience. Audience: Undergraduate Learning Outcomes: 1. Solve a constrained optimization problem by applying calculus rules. Audience: Undergraduate 2. Create and interpret basic data visualizations. Audience: Undergraduate 3. Articulate the law of large numbers as it pertains to empirical economic analysis. Audience: Undergraduate 4. Determine statistical significance of parameter estimates & interpret the results. Audience: Undergraduate 5. Use R for basic calculations and simulations. Audience: Undergraduate 6. Explain statistical concepts to a general audience. Audience: Undergraduate
Sources
- Course catalogue ↗2026-2027