Quantitative Business Analysis:Text and Cases
Published on 16. January 1998
Book
Hardback
672 pages
978-0-256-14713-1 (ISBN)
Description
This text is appropriate for courses entitled 'Management Science', 'Quantitative Business Analysis', 'Quantitative Methods', 'Quantitative Modeling', or other variations of these. The book contains 17 short chapters introducing all the core quantitative tools and techniques of use in analyzing business problems along with 52 class tested cases. The book is based on the highly successful introductory MBA courses at Darden and is distinctive from the standard quantitative text in that the motivation and application of all of the techniques is driven by field-based cases from all the functional areas of business. The text and case volume could be used in a first course at the junior level (most likely as an elective), as a second course following a 'traditional' survey of management science, or in introductory MBA courses.
More details
Language
English
Place of publication
New York
United States
Publishing group
McGraw-Hill Education - Europe
Target group
College/higher education
Illustrations
Illustrations, 1 facsim.
Dimensions
Height: 239 mm
Width: 185 mm
Thickness: 31 mm
Weight
1160 gr
ISBN-13
978-0-256-14713-1 (9780256147131)
Copyright in bibliographic data is held by Nielsen Book Services Limited or its licensors: all rights reserved.
Schweitzer Classification
Persons
Bodily received his PhD (1976) and a masters from MIT in operations research and a BS in physics. He received the Alpha, Iota, Delta award for innovative teaching in 1982, for his work in teaching decision making with new software tools, which evolved into a text published by McGraw-Hill. His area of expertise is decision analysis. Carraway, the other main author, has a PhD from Purdue (1984) in management, an MBA and a BS in math from East Carolina. Pfeifer has a PhD from Georgia Tech (1979)and two Masters in operations research and applied statistics. His widely published work is primarily in regression and forecasting. Frey is the co-author of our dated Vatter et. al., Harvard casebook, Quantitative Methods in Management. He has taught at Harvard for five years after receiving his PhD from Johns Hopkins University (1969) in operations research. He has written a wealth of cases and teaching notes in OR and finance. All of the authors teach the introductory MBA two-course sequence from which this text has been developed. The course is consistently ranked highly by students.
Carraway, the other main author, has a PhD from Purdue (1984) in management, an MBA and a BS in math from East Carolina.
Frey is the co-author of our dated Vatter et. al., Harvard casebook, Quantitative Methods in Management. He has taught at Harvard for five years after receiving his PhD from Johns Hopkins University (1969) in operations research. He has written a wealth of cases and teaching notes in OR and finance.
Pfeifer has a PhD from Georgia Tech (1979)and two Masters in operations research and applied statistics. His widely published work is primarily in regression and forecasting.
Carraway, the other main author, has a PhD from Purdue (1984) in management, an MBA and a BS in math from East Carolina.
Frey is the co-author of our dated Vatter et. al., Harvard casebook, Quantitative Methods in Management. He has taught at Harvard for five years after receiving his PhD from Johns Hopkins University (1969) in operations research. He has written a wealth of cases and teaching notes in OR and finance.
Pfeifer has a PhD from Georgia Tech (1979)and two Masters in operations research and applied statistics. His widely published work is primarily in regression and forecasting.
Content
Part I: FrameworkProactive Decision MakingAlternativesStructuring Assumptions in Decision MakingAssessmentPerformanceRisk ManagementPart II: Evaluating Multiple Performance Measures and RiskEvaluating Multi-Period PerformanceMulti-Objective and Multi-Stakeholder ChoiceRisk Preference and UtilityCompetitor AnalysisProbability DistributionsPart III: Understanding and Assessing UncertaintySamplingTime Series ForecastingRegression: Forecasting Using Explanatory FactorsSimulationPart IV: OptimizationIntroduction to Optimization ModelsThe Mathematics of Optimization