What is Applied Analytics?
How does a large bank differentiate its customers based on credit risk, usage and other important factors, and then target these customers with highly focused offerings? How does a winery quantitatively analyze the appeal of its wines and try to make them better? How do large consumer-goods conglomerates use point-of-sales information to optimize their inventory and save billions of dollars? How do major sports franchises decide on game strategy? The common factor in all these cases is analytics — the sophisticated use of data and quantitative techniques to provide actionable information to an organization. With the guidance and combined expertise of UNT’s professors in Business, Economics, Mathematics and other departments, you could increase your value in the workforce as you engage in a wide variety of courses related to analytics. Even public agencies and academic institutions — almost any type of large organization — need well-trained professionals who know how to efficiently collect, analyze, interpret and present data. Applied Analytics focuses on the practical application of advanced techniques to data rather than on developing theoretical expertise.
How could Applied Analytics help me?
In the Applied Analytics program, we aim to prepare you for a wide variety of employment opportunities, such as data analyst, operations research analyst, quantitative marketing specialist, predictive analyst, research and modeling analyst, statistician and the like. Potential places of employment could include retail and investment banks, healthcare providers, insurance providers, e-commerce portals, airlines, market research firms, sport consulting, telecommunications firms, petroleum and renewable energy industries, institutions of higher education and government agencies including the FBI and the CIA. The next decade and beyond belong to analytics. Professionals in this area will experience high visibility, higher than average salaries and greater mobility between various sectors of the global workforce.
How does it work?
The general requirements for the Applied Analytics concentration are the same as the other Interdisciplinary Studies programs: 30 credit hours required, no more than 18 hours in any one academic area, etc. (see Admissions and Planning); however, only 12 hours may be completed in the G. Brint Ryan College of Business. Courses for credit must be approved by the program coordinator before you register each semester. With the approval of the program coordinator and cooperating departments, you will select classes from Business Analytics (Decision Science), Economics, and an additional related area of interest, such as Educational Psychology, Mathematics, Merchandising, Engineering Systems, Engineering Management or Political Science. Knowledge of at least one foreign language or an acceptable equivalent is required for the Master of Arts degree, but not for the Master of Science.
The academic counselor will help you develop a degree plan that reflects your academic and career goals.
The M.A. or M.S. candidate must complete a minimum of 30 hours from Business Analytics, Economics, and a supporting quantitative or application area, or 24 hours of coursework and six hours of thesis if the student chooses to finish the program with a thesis option. Courses may be selected from the following:
A maximum of 12 hours from the College of Business are permitted.
Students who elect Economics as their primary area must take 6 of the following courses and pass the Econometrics exit exam.
Supporting Quantitative or Application Area that other courses might be drawn from are Geographic Information Systems (GIS), Computer Science, Educational Psychology, Merchandising, Public Administration, etc.
- DSCI 5210 - Model-Based Business Intelligence
- DSCI 5240 - Data Mining
- DSCI 5250 - Statistical Techniques in Simulation
- DSCI 5260 - Business Process Analytics (may be used as a capstone)
- DSCI 5320 - Quality Control
- DSCI 5330 - Enterprise Applications of Business Intelligence
- DSCI 5340 - Predictive Analytics and Business Forecasting
- DSCI 5350 - Big Data Analytics
- DSCI 5360 - Data Visualization Analytics
- ECON 5600 - Mathematical Economics
- ECON 5640 - Multivariate Regression Analysis
- ECON 5645 - Empirical Linear Modeling
- ECON 5650 - Advanced Econometrics
- ECON 5655 - Econometric Analysis of Panel Data
- ECON 5660 - Time Series Econometrics and Forecasting
- ECON 5670 - Applied Econometrics
- INSD 5110 - Introduction to Interdisciplinary Research
- INSD 5940 - Interdisciplinary Capstone Experience
- MATH 5350 - Markov Processes
- MATH 5810 - Probability and Statistics
- MATH 5820 - Probability and Statistics
- MSES 5040 - Analytical Methods for Engineering Systems
- PSCI 6320 - Quantitative Political Research Methods
For further information about a concentration in Applied Analytics at UNT, please contact the Interdisciplinary Studies program coordinator Audra O'Neal at INSD@unt.edu or 940-565-4787.