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An accessible introduction to the essential quantitative methods for making valuable business decisions
Quantitative methods-research techniques used to analyze quantitative data-enable professionals to organize and understand numbers and, in turn, to make good decisions. Quantitative Methods: An Introduction for Business Management presents the application of quantitative mathematical modeling to decision making in a business management context and emphasizes not only the role of data in drawing conclusions, but also the pitfalls of undiscerning reliance of software packages that implement standard statistical procedures. With hands-on applications and explanations that are accessible to readers at various levels, the book successfully outlines the necessary tools to make smart and successful business decisions.
Progressing from beginner to more advanced material at an easy-to-follow pace, the author utilizes motivating examples throughout to aid readers interested in decision making and also provides critical remarks, intuitive traps, and counterexamples when appropriate.
The book begins with a discussion of motivations and foundations related to the topic, with introductory presentations of concepts from calculus to linear algebra. Next, the core ideas of quantitative methods are presented in chapters that explore introductory topics in probability, descriptive and inferential statistics, linear regression, and a discussion of time series that includes both classical topics and more challenging models. The author also discusses linear programming models and decision making under risk as well as less standard topics in the field such as game theory and Bayesian statistics. Finally, the book concludes with a focus on selected tools from multivariate statistics, including advanced regression models and data reduction methods such as principal component analysis, factor analysis, and cluster analysis.
The book promotes the importance of an analytical approach, particularly when dealing with a complex system where multiple individuals are involved and have conflicting incentives. A related website features Microsoft Excel� workbooks and MATLAB� scripts to illustrate concepts as well as additional exercises with solutions.
Quantitative Methods is an excellent book for courses on the topic at the graduate level. The book also serves as an authoritative reference and self-study guide for financial and business professionals, as well as readers looking to reinforce their analytical skills.
- Sales Rank: #1275167 in eBooks
- Published on: 2013-05-29
- Released on: 2013-05-29
- Format: Kindle eBook
From the Back Cover
An accessible introduction to the essential quantitative methods for making valuable business decisions
Quantitative methods—research techniques used to analyze quantitative data—enable professionals to organize and understand numbers and, in turn, to make good decisions. Quantitative Methods: An Introduction for Business Management presents the application of quantitative mathematical modeling to decision making in a business management context and emphasizes not only the role of data in drawing conclusions, but also the pitfalls of undiscerning reliance on software packages that implement standard statistical procedures. With hands-on applications and explanations that are accessible to readers at various levels, the book successfully outlines the necessary tools to make smart and successful business decisions.
Progressing from beginner to more advanced material at an easy-to-follow pace, the author utilizes motivating examples throughout to aid readers interested in decision making and also provides critical remarks, intuitive traps, and counterexamples when appropriate. The book begins with a discussion of motivations and foundations related to the topic, with introductory presentations of concepts from calculus and linear algebra. Next, the core ideas of quantitative methods are presented in chapters that explore introductory topics in probability, descriptive and inferential statistics, and linear regression, followed by a discussion of time series that includes both classical topics and more challenging models. The author also presents linear programming models and decision making under risk as well as less standard topics in the field such as game theory and Bayesian statistics. The book concludes with a focus on selected tools from multivariate statistics, including advanced regression models and data reduction methods such as principal component analysis, factor analysis, and cluster analysis.
The author promotes the importance of an analytical approach, particularly when dealing with a complex system where multiple individuals are involved and have conflicting incentives. A related website features Microsoft Excel� workbooks and MATLAB� scripts to�illustrate concepts, as well as additional exercises with solutions.
Quantitative Methods is an excellent book for courses on the topic at the graduate level. The book also serves as an authoritative reference and self-study guice for financial and business professionals, as well as for readers looking to reinforce their analytical skills.
About the Author
Paolo Brandimarte is Professor of Quantitative Methods for Finance and Logistics at Politecnico di Torino (Italy). He has published numerous journal articles on the application of optimization and simulation methods in different areas, ranging from production management to finance. Dr. Brandimarte is the author of Numerical Methods in Finance and Economics: A MATLAB-Based Introduction, Second Edition and coauthor of Introduction to Distribution Logistics, both published by Wiley.
Most helpful customer reviews
1 of 1 people found the following review helpful.
Excellent Discussion of the Mathematics of Uncertainty and Decisions
By Patrick L. Anderson
Paolo Brandimarte's book on Numerical Analysis was already on my shelf (with a few earmarked pages) when I took a look at his "Quantitative Methods." This book covers a large gap in the mathematical background for a wide variety of decision analytic, uncertainty, risk assessment, and other topics. While there are many books on financial engineering, there are few that provide the basis for understanding such topics as different optimization methods, statistical distributions that can be used to model uncertainty, and unusual (and often barely documented) risk assessment models.
It is, unfortunately, far too common to see professionals and academics inadvertently use a quantitative model as if it was a black box. This certainly lets you peek into, and understand, many of those boxes.
If you need to use, or just want to understand, the mathematics behind many of the more advanced quantitative models in finance, economics, risk assessment, or business management, I recommend this book. If you like to use mathematical software for any of these purposes (in particular, Matlab), this is one of a handful of the most comprehensive on the market.
0 of 0 people found the following review helpful.
Great (but lots of typos)
By Antonio Piemontese
Great book, comprehensive and well-written. Many business examples and applications. The author strives always to reason with you, rather than just exposing topics. All the required background is included for the sake of completeness. Just one drawback: lots of typos, indeed, well beyond the errata corrige list. Some make it difficult to understand the concepts. What a pity ...
0 of 2 people found the following review helpful.
NOT Intro-type Book
By Lydia Jordan
The book is poorly written for the common person to grasp the concepts, and lacks examples to guide the user through problem-solving. You would be better off learning Stats from the various sources available online then to spend $$ for this book. There are also errors in the solutions portion of the book available through a different website. The book is not self-explanatory, is confusing, provides no guidance, and is basically horrible. It fails miserably to be of any help.
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