INTRODUCTION TO ANALYTICS AND DECISION SCIENCE
Decision analysis, linear programming, integer programming, statistical distributions, Markov chains, Monte Carlo simulation, queuing, discrete event simulation. Students will use a variety of tools to investigate applications including transportation networks, revenue management, production scheduling and sports analytics.
Prerequisites & course information
Antirequisite(s): Financial Modelling 3817A/B, Statistical Sciences 4654A/B . Prerequisite(s): 0.5 course from Analytics and Decision Sciences 2288F/G, Data Science 1200A/B, or Statistical Sciences 2864A/B ; and 1.0 courses from any 1000-level courses in Applied Mathematics, Calculus, Mathematics, Numerical and Mathematical Methods, and/or Statistical Sciences. Pre-or Corequisite(s): 0.5 course from: Economics 2122A/B, Economics 2222A/B, Statistical Sciences 2035, Statistical Sciences 2141A/B, Statistical Sciences 2857A/B, or by permission of the School of Management, Economics, and Mathematics. Extra Information: 3 lecture hours, 2 lab hours. Course Weight: 0.50
Sources
- Course catalogue ↗2026-2027