Applied Economic Analytics

The Department of Agricultural and Applied Economics, in the College of Agriculture and Life Sciences, is now offering a graduate-level certificate program in econometric, forecasting, and data analytics tools needed to succeed in modern applied economic management and related fields. This program emphasizes foundational methods spanning economic analysis, data analytics, predictive modeling, and data visualization. An emphasis is placed on relevant business and agribusiness applications. The certificate prepares students by allowing them to develop high-level skills that span applied economics, agribusiness management, and data analytics.

Program features

• 100 percent online and asynchronous
• Four 3-credit graduate courses
• Access to expert faculty
• Time to complete: In most cases four semesters. 
• Degree-seeking students may take courses in conjunction with their regular course load. 
• Non-degree seeking, full-time students can complete the certificate in two-to-three semesters. 
• Non-degree seeking, part-time students, taking one course per semester, can complete the certificate in four semesters. 

Program goals and outcomes

Students who complete the certificate program will be able to:

• Apply statistical properties and probability theory to agribusiness and applied economic data.
• Employ advanced computational, statistical, simulation, and data visualization resources using modern statistical computing packages and tools. 
• Construct and implement mathematical optimization models relevant to applied economic decision-making.
• Estimate statistical and econometric models for applied economic and agribusiness decision-making.
• Formulate, specify, and estimate modern forecasting models.
• Interpret statistical and econometric results from business, government, and academic research.
• Evaluate the statistical integrity of predictive models and the accuracy of alternative forecasting methods.
• Apply regression trees and machine learning methods to structured and unstructured data sets.