Jeffrey M. Keisler

Prescriptive Analytics (eBook, PDF)

Mastering the Spreadsheet of Everything

• Format: PDF

Produktbeschreibung

Prescriptive Analytics: Mastering the Spreadsheet of Everything combines the quantitative decision-informing techniques of management science and operations research with the data-centric techniques found throughout the world of analytics. The material uses only standard Excel spreadsheet features and functions for creating models and then applying sensitivity, scenario, simulation, decision, and optimization analysis.

How can we make high quality decisions in an increasingly data-rich but also uncertain and complex world? This book provides the answer, preparing you for the prescriptive analytic future. Gilberto Montibeller, Professor of Operations Management, University of Bristol.

An important book. It will be invaluable in entry-level courses in prescriptive analytics and all related fields. Robert Bordley, Director, Systems Engineering and Design Program, University of Michigan

Rooted in a rigorous decision framework, one of the most intuitive and accessible journeys into the world of prescriptive analytics. Victor Podinovski, Head of Management Science and Operations Group, Loughborough University

A remarkable in-depth treatment of implementing complex analytical formulations using spreadsheets in a simple and accessible way. Ali Abbas, Founding Director of the Neely Center for Ethical Leadership and Decision-Making, University of Southern California

A fresh and pragmatic approach to the challenges of developing analytical thinkers - and doers. Students will quickly add useful tools, and they'll start to connect the dots of the bigger picture. Patrick Noonan, Emeritus Professor of Management & Decision Sciences. Emory University

This book starts the study of analytics with a simple problem and a few basic Excel formulas, and staying within that framework and emphasizing comprehension, builds up to cover all of the mainstream analytic topics and some very advanced ones as well. Janet Wagner, Founding Dean, School of Business, Stockton University

The perfectly illustrated examples, with tips, tricks, and aids to all possible roadblocks a student might encounter, seamlessly take you from zero to master's level skill on mechanics of spreadsheet modeling. Avipsa Acharya (former student), Business Data Analyst, State Street Corp.

Professor Keisler's amazing book gives everyone analytics skills for success. Igor Linkov, Senior Scientific and Technical Manager, US Army Corps of Engineers

I really wish to congratulate Dr. Keisler on having written such a substantial book. This book gives a very accessible and well-founded introduction to a broad range of analytical techniques for guiding business and engineering decisions. Ahti Salo, Director, Systems Analysis Laboratory, Aalto University

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Produktdetails

• Verlag: Springer Nature Switzerland
• Seitenzahl: 259
• Erscheinungstermin: 24. August 2024
• Englisch
• ISBN-13: 9783031593536
• Artikelnr.: 72243789

Autorenporträt

Jeffrey M. Keisler (MBA Chicago, PhD Harvard) is Professor of Management Science & Information Systems at University of Massachusetts Boston. He was President of the INFORMS Decision Analysis Society and founding Secretary of the former Spreadsheet Research Section at INFORMS. He was named a Fellow of the Society for Risk Analysis, a Fellow of the Society for Decision Professionals, and a Fulbright Distinguished Chair. He has published nearly 90 journal articles and several books and is a long-time associate editor for several INFORMS and EURO journals. Over 30+ years in industry, government, consulting and academia, he has been applying, implementing, developing, teaching and preaching spreadsheet tools and prescriptive analytics techniques.

Inhaltsangabe

1. Modeling.- 2. Sensitivity Analysis.- 3. Indexed Sensitivity Analysis.- 4. Scenario Analysis.- 5. Simulation Analysis.- 6. Customized Input Distributions.- 7. Decision Analysis - Expected Value Maximization.- 8. Decision Analysis - Advanced Topic.- 9. Optimization: Decisions With Constraints.- 10. Optimization: Excel Solver.- 11. Epilogue.