Brandimarte - Quantitative Methods

Quantitative Methods

Copyright 2011 by John Wiley & Sons, Inc. All rights reserved

Published by John Wiley & Sons, Inc., Hoboken, New Jersey
Published simultaneously in Canada

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Library of Congress Cataloging-in-Publication Data :

Brandimarte, Paolo.
Quantitative methods : an introduction for business management / Paolo Brandimarte.
p. cm.
Includes bibliographical references and index.
ISBN 978-0-470-49634-3 (hardback)
1. ManagementMathematical models. I. Title.
HD30.25.B728 2011
658.0072-dc22
2010045222

Preface

And there I was, waiting for the big door to open, the big door that stood between me and my archnemesis. I found little comfort and protection, if any, sitting in what seemed my thin tin tank, looking around and searching for people in my same dire straits. Then, with a deep rumble, the big steel door of the ship opened, engines were started, and I followed the slow stream of cars. I drove by rather uninterested police officers, and there it was, my archnemesis: the first roundabout in Dover.

For European continental drivers like me, used to drive on the right side of the street (and yes, I do mean right ), the first driving experience in the Land of Albion has always been a challenge. That difficulty compounded with the lack of roundabouts in Italy at the time, turning the whole thing into sheer nightmare. Yet, after a surprisingly short timespan, maybe thanks to the understanding and discipline of the indigenous drivers, I got so used to driving there, and to roundabouts as well, that after my return to Calais I found driving back in supposedly familiar lanes somewhat confusing.

I had overcome my fear, but I am digressing, am I? Well, this book should indeed be approached like a roundabout: There are multiple entry and exit points, and readers are expected to take their preferred route among the many options, possibly spinning a bit for fun. I should also mention that, however dreadful that driving experience was to me, it was nothing compared with the exam labor of my students of the terrifying quantitative methods course. I hope that this book will help them, and many others, to overcome their fear. By the same token, I believe that the book will be useful to practitioners as well, especially those using data analysis and decision support software packages, possibly in need of a better understanding of those black boxes.

I have a long teaching experience at Politecnico di Torino, in advanced courses involving the application of quantitative methods to production planning, logistics, and finance. A safe spot, indeed, with a fairly homogeneous population of students. Add to this the experience in teaching numerical methods in quantitative finance masters programs, with selected and well-motivated students. So, you may imagine my shock when challenged by more generic and basic courses within a business school (ESCP Europe, Turin Campus), which I started teaching a few years ago. The subject was quite familiar, quantitative methods, with much emphasis on statistics and data analysis.

However, the audience was quite different, as the background of my new students ranged from literature to mathematics/engineering, going through law and economics. When I wondered about how not to leave the whole bunch utterly disappointed, the mission impossible theme started ringing in my ears. I must honestly say that the results have been occasionally disappointing, despite my best efforts to make the subject a bit more exciting through the use of business cases, a common mishap for teachers of technical subjects at business schools. Yet, quite often I was delighted to see apparently hopeless students struggle, find their way, and finally pass the exam with quite satisfactory results. Other students, who had a much stronger quantitative background, were nevertheless able to discover some new twists in familiar topics, without getting overly bored. On the whole, I found that experience challenging and rewarding.

On the basis of such disparate teaching experiences, this possibly overambitious book tries to offer to a hopefully wide range of readers whatever they need.

• Part I consists of three chapters. Chapter 1 aims at motivating the skeptical ones. Then, I have included two chapters on calculus and linear algebra. Advanced readers will probably skip them, possibly referring back to refresh a few points just when needed, whereas other students will not be left behind. Not all the material provided there is needed; in particular, the second half of Chapter 3 on linear algebra is only necessary to tackle Parts III and IV.
• Part II corresponds to the classical core of a standard quantitative methods course. Chapters 410 deal with introductory topics in probability and statistics. Readers can tailor their way through this material according to their taste. Especially in later chapters, they can safely skip more technical sections, which are offered to more mathematically inclined readers. Both Chapter 9, on inferential statistics, and Chapter 10, on linear regression, include basic and advanced sections, bridging the gap between cookbook-oriented texts and the much more demanding ones. Also Chapter 11, on time series, consists of two parts. The first half includes classical topics such as exponential smoothing methods; the second half introduces the reader to more challenging models and is included to help readers bridge the gap with the more advanced literature without getting lost or intimidated.