DATA 610 - Essentials of Business Analytics

3 Credits
This course introduces advanced methods of building statistical models for decision-makers, with a primary focus on modeling techniques such as logistic regression and discriminant analysis. Students solve real-world business cases, applying statistical concepts and techniques in business, finance, market research, and healthcare management contexts.

Course Learning Outcomes:
1. Produce analytical reports to identified industry standards.
2. Solve linear and non-linear optimization problems using data analytic software applications.
3. Interpret results of estimated linear regression, time series, and forecasting models to inform business decision making.
4. Perform Monte Carlo Simulations to mathematically model and make decisions under uncertain conditions.
5. Interpret descriptive statistics in predictive and prescriptive application-based scenarios.
6. Select appropriate data visualization techniques to communicate findings.
7. Explain the relevance of big data analytics in various business applications.