MAA 616 - Stochastic Modeling for Analytics

Course unit(s): 1
How do companies and organizations use data to forecast what may lie ahead? Students will learn in this course the importance of stochastic methods and how probability and randomness are keys to simulation modeling. Applications of stochastic processes include the analysis of stock market results and trends, vital medical information, seismology, and weather research. Students will learn via real-life case studies and methods such as the Markov chain. Students will learn how to use historical data to understand the likelihood of what may happen in the future using robust stochastic models.