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Spreadsheet Modeling and Decision Analysis : A Practical Introduction to Business Analytics / Cliff T. Ragsdale

By: Material type: TextTextPublication details: Delhi Cengage Learning India Pvt. Ltd. 2018Edition: 8th EdDescription: xviii, 845p. : ill. ; 25cmISBN:
  • 9789353502225
Subject(s): DDC classification:
  • 23rd 658.40300285554 RAG
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Item type Current library Call number Status Notes Date due Barcode
Reference Book VIT-AP General Stacks 658.40300285554 RAG (Browse shelf(Opens below)) Not for loan MGT 019251
Text Book VIT-AP General Stacks 658.40300285554 RAG (Browse shelf(Opens below)) Checked out to Kashif Beg (70580) MGT 2025-07-28 019252
Text Book VIT-AP General Stacks 658.40300285554 RAG (Browse shelf(Opens below)) In transit from VIT-AP to School of Business & General Section since 2025-01-29 MGT 019344

Written by the innovator of the spreadsheet teaching revolution and highly regarded leader in business analytics, Cliff Ragsdale’s new edition of SPREADSHEET MODELING AND DECISION ANALYSIS: A PRACTICAL INTRODUCTION TO BUSINESS ANALYTICS retains the elements and philosophy of past success while now helping your students transition to business analytics. SPREADSHEET MODELING AND DECISION ANALYSIS, 8E’s updates work seamlessly with Microsoft® Office Excel® 2016. Succinct instruction highlights the most commonly used business analytics techniques and clearly demonstrates how to implement these tools with the most current version of Excel® for Windows. This text focuses on developing both algebraic and spreadsheet modeling skills. This edition now features Analytic Solver and XLMiner Platforms with powerful tools for performing optimization, simulation and decision analysis in Excel, as well as complete tools for performing data mining in Excel and techniques for predictive analytics.
Features:

XLMINER PLATFORM OFFERS A COMPLETE SUITE OF TOOLS FOR HANDS-ON EXPERIENCE. This leading business analytics software provides a variety of data mining tools and techniques including data import and cleansing, data exploration and visualization, feature selection, clustering, affinity analysis. Students also find a variety of techniques for predictive analytics including discriminant analysis, neural networks, logistic regression, classification and regression trees, k-nearest neighbor, naïve Bayes, and times-series analysis.
UPDATED CONTENT REFLECTS MICROSOFT® OFFICE EXCEL® 2016. This timely coverage provides students with the most current information for dealing with key business analytics decision making problems.
ALGEBRAIC FORMULATIONS AND SPREADSHEETS ARE USED SIDE-BY-SIDE TO HELP DEVELOP CONCEPTUAL THINKING SKILLS. Step-by-step instructions and numerous annotated screenshots make examples easy to follow and understand.
ANALYTIC SOLVER PLATFORM PROVIDES HANDS-ON EXPERIENCE WITH STATE-OF-THE-ART BUSINESS ANALYTICS SOFTWARE. Powerful tools in the Analytic Solver Platform enable students to perform optimization and simulation and work with decision trees in Excel. This tool also provides the capabilities for performing simulation optimization and robust optimization methods.
THE LATEST VERSION OF MICROSOFT EXCEL 2016 IS FEATURED THROUGHOUT. All screen shots and instructions throughout this edition reflect the latest version of Excel to prepare your students with the contemporary skills they will need.
EXPANDED DISCUSSION EMPHASIZES GOOD DECISION MAKING. This key discussion in Chapter 1 clearly defines good decision making while updated examples highlight successful applications of business analytics in large organizations.
NEW COVERAGE HIGHLIGHTS THE LINE BALANCING PROBLEM. New, key material in Chapter 6 (Integer Linear Programming) provides a new example of integer programming that is interesting, challenging, and practical.
MAJOR UPDATES REFLECT CHANGES IN THE XLMINER PLATFORM SOFTWARE. Coverage in Chapter 10 (Data Mining) now also covers ROC and AUC graphs as well as the concepts of precision, recall, specificity, and the F1 score.
NEW AND REVISED END-OF-CHAPTER QUESTIONS CHECK READER UNDERSTANDING. New question and application opportunities throughout the book ensure students understand key principles.

About the Author:
Cliff Ragsdale, Virginia Polytechnic Institute and State University

A recognized innovator in spreadsheet instruction and highly regarded pioneer in business analytics, Dr. Cliff Ragsdale is the Bank of America Professor of Business Information Technology and Academic Director of the Center for Business Intelligence and Analytics in the Pamplin College of Business at Virginia Tech, where he has taught since 1990. Dr. Ragsdale received his Ph.D. in Management Science and Information Technology from the University of Georgia. He also holds an M.B.A. in Finance and B.A. in Psychology from the University of Central Florida. Before pursuing his Ph.D., he was supervisor of Benefit Finance & Qualified Plans at the international headquarters of Red Lobster, Inc. He has served as an information systems and statistical consultant for a variety of companies and as an expert witness in the area of spreadsheet forensics. Dr. Ragsdale's primary areas of research interest include applications of artificial intelligence, mathematical programming, and applying statistics to business problems. His research has appeared in Decision Sciences, Naval Research Logistics, Omega: The International Journal of Management Science, Computers & Operations Research, Operations Research Letters, Personal Financial Planning, and other publications. He has received both the Pamplin award for excellence in teaching and the Outstanding Doctoral Educator Award from the Pamplin College of Business Administration at Virginia Tech. Dr. Ragsdale is a Fellow of the Decision Sciences Institute and active member of DSI and INFORMS.

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