Course Description
Quantitative methods for agribusiness management focused on seven topics: statistical tests, regression, forecasting, linear programming, non-linear optimization, multi-criteria decision making, and simulation models. These tools are introduced in online lecture modules and then put to practical use using SAS and Excel.
Athena Title
Quant Methods for Agribus Mgmt
Equivalent Courses
Not open to students with credit in AAEC 6630
Non-Traditional Format
This course will be taught 95% or more online.
Semester Course Offered
Offered fall
Grading System
A - F (Traditional)
Course Objectives
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 misspecifiction. 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. Multivariate Regression V. Forecasting VI. Linear Programming VIII. Distribution and Network Models IX. Integer Progrmaming X. Non-Linear Optimization XI. Multi-Criteria Decision Making XII. Simulation
Syllabus