Mathematical Decision Making: Predictive Models and Optimization | The Great Courses
English | Size: 1.26 GB
Category: CBT
Professor Scott P. Stevens, Ph.D.
James Madison University
Not so long ago, executives faced with complex problems made decisions based on experience, intuition, and no small measure of luck. But now there’s a better way. In recent decades, mathematics and computer science have perfected formerly top-secret techniques for predicting the best possible outcomes when faced with conflicting options. This field goes by different names-analytics, operations research, linear and nonlinear programming, management science-but its purpose is simple: to apply quantitative methods to help business managers, public servants, investors, scientific researchers, and problem solvers of all kinds make better decisions.
Mathematical Decision Making: Predictive Models and Optimization is your guide, teaching you the major mathematical techniques, applications, and spreadsheet procedures for basic analytics in 24 information-packed half-hour lectures. Your professor is award-winning educator Scott Stevens, Professor of Computer Information Systems and Business Analytics at James Madison University.
Those who will benefit from Professor Stevens’s engaging presentation include:
• managers eager to make better decisions-whether in business, technical, or non-profit
endeavors;
• professionals aspiring to advance in their careers by mastering a proven approach to
problem solving;
• those who work with or review spreadsheet and graphical presentations, and need to be
able to separate good data from bad;
• students in business, mathematics, finance, marketing, health care, engineering, urban
planning, and a host of other fields;
• math lovers curious to see a field that is often the opposite of calculus: simple functions and
complex boundary conditions, instead of complex functions with simple boundary conditions;
• lifelong learners who want to hone their critical thinking skills with important analytical
techniques, made accessible and intellectually exciting as never before.
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