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Quantitative Methods: An Introduction for Business Management
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 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.
912 pages, Hardcover
First published April 26, 2011
20 people want to read
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February 6, 2016
This is a math book with some business and economic examples included. A better subtitle and explanation would be “The math you need to know to use and understand advanced quantitative methods in business.” The book is split into sections and a look at the 16 chapter titles after the introductory first chapter will explain a great deal. They are:
*) Calculus
*) Linear algebra
*) Descriptive statistics
*) Probability theories
*) Discrete random variables
*) Continuous random variables
*) Dependence, correlation and conditional expectation
*) Inferential statistics
*) Simple linear regression
*) Deterministic decision models
*) Decision making under risk
*) Multiple decision makers, subjective probability and other wild beasts
*) Introduction to multivariate analysis
*) Advanced regression models
*) Dealing with complexity: Data reduction and clustering
The author presupposes that the reader is very familiar with the topics before the chapter is encountered. There is no slack cut in terms of the level of difficulty of the mathematics. When a topic is first stated, it is as a reminder and not as a review. As the list and number of pages indicate, this is a book for a two or three semester course sequence in the mathematics used in high level quantitative methods used in business.
Fundamentally, it is a text for courses designed for people that are math majors moving into quantitative business management. For that, it is an excellent book. Unlike some other books, no one can criticize this one for being weak on the math, I would suspect that the students using it would argue the contrary.
This book was made available for free for review purposes
*) Calculus
*) Linear algebra
*) Descriptive statistics
*) Probability theories
*) Discrete random variables
*) Continuous random variables
*) Dependence, correlation and conditional expectation
*) Inferential statistics
*) Simple linear regression
*) Deterministic decision models
*) Decision making under risk
*) Multiple decision makers, subjective probability and other wild beasts
*) Introduction to multivariate analysis
*) Advanced regression models
*) Dealing with complexity: Data reduction and clustering
The author presupposes that the reader is very familiar with the topics before the chapter is encountered. There is no slack cut in terms of the level of difficulty of the mathematics. When a topic is first stated, it is as a reminder and not as a review. As the list and number of pages indicate, this is a book for a two or three semester course sequence in the mathematics used in high level quantitative methods used in business.
Fundamentally, it is a text for courses designed for people that are math majors moving into quantitative business management. For that, it is an excellent book. Unlike some other books, no one can criticize this one for being weak on the math, I would suspect that the students using it would argue the contrary.
This book was made available for free for review purposes
Displaying 1 of 1 review