Data, Models, and Decisions: The Fundamentals of Management Science
South-Western College Pub., 2000 - Business & Economics - 530 pages
The book combines topics from two traditionally distinct quantitative subjects: probability/statistics and optimization models, into one unified treatment of quantitative methods and models for management and business. The book stresses those fundamental concepts that are most important for the practical analysis of management decisions: modeling and evaluating uncertainty explicitly, understanding the dynamic nature of decision-making, using historical data and limited information effectively, simulating complex systems, and allocating scarce resources optimally.
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Brief Table of Contents CHAPTER 1 DECISION ANALYSIS
FUNDAMENTALS OF DISCRETE PROBABILITY
CONTINUOUS PROBABILITY DISTRIBUTIONS AND THEIR APPLICATIONS
10 other sections not shown
advertising aircraft airline analysis assets average binary binomial distribution cell codfish column compute confidence interval Conley Fisheries Construct contribution to earnings correlation cost customers decision tree decision variables demand denote discrete optimization discrete optimization model equation estimate event example EXERCISE expected return f-distribution feasible region Filatoi Riuniti flight formula independent variables investment isoquant linear optimization model linear regression linear regression model machine capacity manufacturing million month mtons node nonlinear optimization model Nonnegativity Normal distribution obeys a Normal objective function observed sample mean operations optimal solution optimization problems pliers portfolio predict probability density function probability distribution production profit put options Q-Class random number random variable regression coefficients residuals revenue Rockport sample mean sample standard deviation shadow price shown in Figure shown in Table simulation model solve Solver spreadsheet standard Normal steel Suppose Sytech tion unit wrenches Y-Class