Course Description
Quantitative methods for agribusiness management focused on seven topics, including statistical tests, regression, forecasting, linear programming, non-linear optimization, multi- criteria decision making, and simulation models. These tools are introduced in lecture and then put to practical use in the computer lab using SAS and Excel.
Athena Title
Quant Tools for Agribus Mgmt
Equivalent Courses
Not open to students with credit in AAEC 6630E
Prerequisite
AAEC 6580-6580L
Semester Course Offered
Offered fall
Grading System
A - F (Traditional)
Course Objectives
Learning Outcomes: 1. A fundamental understanding of multivariate regression analysis and forecasting techniques, including measures of model performance and robustness, interpretation of model results, and the consequences of model misspecification. 2. Familiarity with basic procedures and commands for data management and analysis in SAS. 3. A thorough understanding of linear and non-linear programming, multi-criteria decision analysis and simulation models, including model design, data requirements, and sensitivity analysis. 4. A toolbox of common statistical tests, including common statistical tests (e.g., t-tests, ANOVA) and when and how to use alternative tests (e.g., Wilcoxon Signed Test, Rank-Sum Test, Welch t-test).
Topical Outline
I. Common Statistics II. Not-as-Common Statistics III. ANOVA IV. Multi-variate Regression V. Forecasting VI. Linear Programming VII. Distribution and Network Models VIII. Integer Progrmaming IX. Non-Linear Optimization X. Multi-criteria Decision Making XI. Simulation