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Business Statistics for Competitive Advantage with Excel 2016

Basics, Model Building, Simulation and Cases

  • Textbook
  • © 2016

Overview

  • Cutting-edge coverage of Excel 2016 for use in business school classrooms and beyond

  • New real-world examples and assignments on global markets incorporated throughout

  • Focuses on statistical analysis, model building, simulation, sensitivity analysis, and translation of results to improve business decisions

  • Covers the full gamut of Excel properties and utilities for Business Statistics, including time-saving shortcuts communicated very clearly with concise tables and screen shots

  • Statistical Analyses are translated into concise business English applications that are taken from actual business problems

  • Includes supplementary material: sn.pub/extras

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Table of contents (14 chapters)

Keywords

About this book

The revised Fourth Edition of this popular textbook is redesigned with Excel 2016 to encourage business students to develop competitive advantages for use in their future careers as decision makers. Students learn to build models using logic and experience, produce statistics using Excel 2016 with shortcuts, and translate results into implications for decision makers. The textbook features new examples and assignments on global markets, including cases featuring Chipotle and Costco. A number of examples focus on business in emerging global markets with particular emphasis on emerging markets in Latin America, China, and India. Results are linked to implications for decision making with sensitivity analyses to illustrate how alternate scenarios can be compared.  

The author emphasises communicating results effectively in plain English and with screenshots and compelling graphics in the form of memos and PowerPoints. Chapters include screenshots to make it easy to conduct analyses in Excel 2016. PivotTables and PivotCharts, used frequently in business, are introduced from the start. The Fourth Edition features Monte Carlo simulation in four chapters, as a tool to illustrate the range of possible outcomes from decision makers’ assumptions and underlying uncertainties. Model building with regression is presented as a process, adding levels of sophistication, with chapters on multicollinearity and remedies, forecasting and model validation, auto-correlation and remedies, indicator variables to represent segment differences, and seasonality, structural shifts or shocks in time series models. Special applications in market segmentation and portfolio analysis are offered, and an introduction to conjoint analysis is included. Nonlinear models are motivated with arguments of diminishing or increasing marginal response.

Authors and Affiliations

  • McIntire School of Commerce, University of Virginia, Charlottesville, USA

    Cynthia Fraser

About the author

Cynthia Fraser received her Ph.D. from The Wharton School, University of Pennsylvania, and is a member of the Marketing faculty at The McIntire School of Commerce, University of Virginia, where she teaches business statistics.  Her research has appeared in a number of journals, including Decision Science, Management Science, Journal of Marketing, Journal of Consumer Research, Psychology and Marketing, Journal of International Business Studies, and Journal of Applied Social Psychology.

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