Apr 13, 2024  
2023-2024 Graduate Catalog 
    
2023-2024 Graduate Catalog

Applied Economics and Predictive Analytics, M.S.A.E.P.A.


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The M.S. in applied economics and predictive analytics degree is designed to help meet the burgeoning demand for analytics training on the part of business, government and nonprofits. This degree focuses on economic analysis and decision-making along with strong quantitative training, and brings additional skills not typically provided in analytics programs found in statistics, engineering or business programs. “Predictive analytics” refers to the process of building models that predict consumer behaviors under different circumstances and help customize product offerings that better suit the tastes and preferences of consumers; “predictive analytics” also refers to building models to predict time series variables of importance to businesses and governments (e.g., product sales and tax revenues) and to evaluate competing government programs and business strategies. The M.S. is a 30 credit hour degree.

Admission Requirements

The minimum admission requirements for the M.S. in applied economics and predictive analytics are as follows:

  1. Undergraduate cumulative GPA of at least 3.000 (on a 4.000 scale).
  2. Twelve credit hours of undergraduate economics, including two intermediate theory courses, one in microeconomics and one in macroeconomics.
  3. An introductory course in statistics.
  4. One term of calculus.
  5. Satisfactory GRE graduate school admission test scores if the undergraduate GPA is lower than 3.000.

Degree Requirements


The M.S. in applied economics and predictive analysis is a 30-credit hour degree.

Required Core Courses (9 Credit Hours)


Required Advanced Analytics Courses (6 Credit Hours)


Required Business Intelligence Courses (3 Credit Hours)


One course from the following:

Total: 30 Credit Hours


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