E-Book Overview
This book focuses on the use of quantitative methods for both business and management, helping readers understand the most relevant quantitative methods for managerial decision-making. Pursuing a highly practical approach, the book reduces the theoretical information to a minimum, so as to give full prominence to the analysis of real business problems. Each chapter includes a brief theoretical explanation, followed by a real-life managerial case that needs to be solved, which is accompanied by a corresponding Microsoft Excel® dataset. The practical cases and exercises are solved using Excel, and for each problem, the authors provide an Excel file with the complete solution and corresponding calculations, which can be downloaded easily from the book’s website. Further, in an appendix, readers can find solutions to the same problems, but using the R statistical language. The book represents a valuable reference guide for postgraduate, MBA and executive education students, as it offers a hands-on, practical approach to learning quantitative methods in a managerial context. It will also be of interest to managers looking for a practical and straightforward way to learn about quantitative methods and improve their decision-making processes.
E-Book Content
Miguel Ángel Canela · Inés Alegre · Alberto Ibarra
Quantitative Methods for Management A Practical Approach
Quantitative Methods for Management
Miguel Ángel Canela • Inés Alegre Alberto Ibarra
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Quantitative Methods for Management A Practical Approach
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Miguel Ángel Canela IESE Business School Barcelona, Spain
Inés Alegre IESE Business School Barcelona, Spain
Alberto Ibarra IPADE Business School Mexico City, Mexico
ISBN 978-3-030-17553-5 ISBN 978-3-030-17554-2 https://doi.org/10.1007/978-3-030-17554-2
(eBook)
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Preface
More than ever, managers are expected to perform data-driven decision-making in their organizations. We intend to contribute to that trend with a short book which presents some quantitative methods which are frequently used in managerial settings. Recent developments in the software industry have greatly enlarged the computational capabilities for data analysis purposes. This has facilitated incorporating quantitative methods into all business areas in order to solve interesting questions such as do we have a gender pay-gap in our firm? Can we