Quantitative methods for business

David R. Anderson (University of Cincinnati), Dennis J. Sweeney (University of Cincinnati), Thomas A. Williams (Rochester Institute of Technology), Jeffrey D. Camm (University of Cincinnati), James J. Cochran (University of Alabama), Michael J. Fry (University of Cincinnati), Jeffrey W. Ohlmann (University of Iowa)

You don't have to be a mathematician to maximize the power of quantitative methods. Written for the current or future, business professional, Quantitative Methods for Business, 13th Edition makes it easy for you to understand how you can most effectively use quantitative methods to make smart, successful decisions. The book's hallmark problem-scenario approach guides you step by step through the application of mathematical concepts and techniques. Memorable real-life examples demonstrate how and when to use the methods found in the book, while instant online access provides you with Excel worksheets, LINGO, and the Excel add-in Analytic Solver Platform. The chapter on simulation includes a more elaborate treatment of uncertainty by using Microsoft Excel to develop spreadsheet simulation models. The new edition also includes a more holistic approach to variability in project management. Completely up to date, Quantitative Methods for Business, 13th Edition reflects the latest trends, issues, and practices from the field

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Year of publication:	[2016] ; 13. edition
Authors:	Anderson, David Ray ; Sweeney, Dennis J. ; Williams, Thomas Arthur ; Camm, Jeffrey D. ; Cochran, James J. ; Fry, Michael J. ; Ohlmann, Jeffrey W.
Publisher:	Boston, MA, USA : Cengage Learning
Subject:	Betriebswirtschaftslehre \| Business economics \| Statistische Methodenlehre \| Statistical theory \| Management \| Quantitative Methode \| Entscheidungstheorie
Description of contents:	Table of Contents [gbv.de]

Extent:	xxii, 914 Seiten Illustrationen 26 cm
Type of publication:	Book / Working Paper
Language:	English
Notes:	Most illustrations in blue, gray, and black. - Includes bibliographical references (pages 844-845) and index Introduction to probability Probability distributions Decision analysis Utility and game theory Time series analysis and forecasting Introduction to linear programming Linear programming: sensitivity analysis and interpretation of solution Linear programming applications in marketing, finance, and operations management Distribution and network models Integer linear programming Advanced optimization applications Project scheduling: PERT/CPM Inventory models Waiting line models Simulation Markov processes
ISBN:	978-1-285-86631-4 ; 1-285-86631-2
Source:	ECONIS - Online Catalogue of the ZBW

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