Quantitative methods an introduction for business management
"This book consists of the following four parts: Motivations and Foundations; Elementary Probability and Statistics; Decision Making Models; and Advanced Statistical Modeling. Part I is introductory, and an initial chapter provides motivation for all of the subsequent chapters by means of simple, but (hopefully) well-thought, toy examples. The following two chapters lay down necessary foundations in calculus and algebra. Part II consists of a classical course in probability and statistics, and the author stresses the use of many examples and counter-examples. Part III addresses decision making since probability and statistics are used to make decisions. Deterministic models, i.e. typical LP models, are introduced, and the emphasis is on modeling rather than computation by the simplex method. Emphasis is also placed on risk aversion and risk measures, and the author illustrates portfolio management as a main motivator. Part IV builds on Part II and discusses a few multivariate analysis models. To help less mathematically inclined readers, each chapter in Part IV contains an initial section that illustrates and motivates each approach without delving into too many details. These readers may wish to skip the remainder of each chapter. The book's companion Web site includes Microsoft Office Excel workbooks to illustrate concepts. In addition, MATLAB files, additional exercises with solutions are provided online"--
""This book consists of the following four parts: Motivations and Foundations; Elementary Probability and Statistics; Decision Making Models; and Advanced Statistical Modeling. Part I is introductory, and an initial chapter provides motivation for all of the subsequent chapters by means of simple, but (hopefully) well-thought, toy examples. The following two chapters lay down necessary foundations in calculus and algebra. Part II consists of a classical course in probability and statistics, and the author stresses the use of many examples and counter-examples. Part III addresses decision making since probability and statistics are used to make decisions. Deterministic models, i.e. typical LP models, are introduced, and the emphasis is on modeling rather than computation by the simplex method. Emphasis is also placed on risk aversion and risk measures, and the author illustrates portfolio management as a main motivator. Part IV builds on Part II and discusses a few multivariate analysis models. To help less mathematically inclined readers, each chapter in Part IV contains an initial section that illustrates and motivates each approach without delving into too many details. These readers may wish to skip the remainder of each chapter. The book's companion Web site includes Microsoft Office Excel workbooks to illustrate concepts. In addition, MATLAB files, additional excercises with solutions are provided online"--"
""This book consists of the following four parts: Motivations and Foundations; Elementary Probability and Statistics; Decision Making Models; and Advanced Statistical Modeling. Part I is introductory, and an initial chapter provides motivation for all of the subsequent chapters by means of simple, but (hopefully) well-thought, toy examples. The following two chapters lay down necessary foundations in calculus and algebra. Part II consists of a classical course in probability and statistics, and the author stresses the use of many examples and counter-examples. Part III addresses decision making since probability and statistics are used to make decisions. Deterministic models, i.e. typical LP models, are introduced, and the emphasis is on modeling rather than computation by the simplex method. Emphasis is also placed on risk aversion and risk measures, and the author illustrates portfolio management as a main motivator. Part IV builds on Part II and discusses a few multivariate analysis models. To help less mathematically inclined readers, each chapter in Part IV contains an initial section that illustrates and motivates each approach without delving into too many details. These readers may wish to skip the remainder of each chapter. The book's companion Web site includes Microsoft Office Excel workbooks to illustrate concepts. In addition, MATLAB files, additional exercises with solutions are provided online"--"@en
"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. iQuantitative Methods: An Introduction for Business Management/i 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 Excelspan style="font-family: "/span workbooks and MATLABspan style="font-family: "/span scripts to illustrate concepts as well as additional exercises with solutions./ iQuantitative Methods/i 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."@en
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