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This Book Is Designed To Serve As A Text For Management, Economics, Accountancy (Chartered And Cost Accountancy), And Commerce Students. The Book Covers Concepts, Illustrations And Problems In Statistics And Operations Research. Part I Deals With Statistical Techniques For Decision Making. Part Ii Studies Various Operations Research Techniques For Managerial Decisions.The Book Contains Illustrations And Problems, Drawn Extensively From Various Functional Areas Of Management, Viz., Production, Finance, Marketing And Personnel, Which Are Designed To Understand Real Life Decision Making Situations. In Order To Make The Book Self-Contained, All Relevant Mathematical Concepts And Their Applications Have Been Included. To Enhance The Understanding Of The Subject Matter By The Students Belonging To Different Disciplines, The Approach Adopted In This Book, Both In Statistics And Operations Research, Is Conceptional Rather Than Mathematical. Hence Complicated Mathematical Proofs Have Been Avoided.This Book Would Be An Ideal Reference To Executives, Computer Professionals, Industrial Engineers, Economic Planners And Social Scientists. The Other Books By The Same Authors Are: Operations Research For Management And Business Statistics.
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.
This thoroughly revised and well-received book, now in its Fourth Edition, continues to give an in-depth and incisive analysis of the various mathematical techniques required for managers in their decision-making process. The book provides a clear understanding of the practical utility of mathematical modelling and techniques, such as linear programming, integer programming, goal programming, dynamic programming, inventory models, decision theory, game theory, network analysis, queuing, simulation and Markov analysis, for solving real-life problems. The book lays emphasis on the practical applications of the techniques rather than their rigorous mathematical treatment. It also discusses probability and probability distributions--essential to tackling the everyday uncertainties of life. The book is primarily intended as a textbook for undergraduate and postgraduate students of management, postgraduate students of commerce, students of Master of Financial Control (MFC) course, and undergraduate students of industrial and production engineering. In addition, practising managers will also find the book immensely helpful in their day-to-day decision-making process. New to This Edition: A section describing the construction of activity on node (AON) networks for CPM and PERT networks has been included considering that most software designed for network analysis plot networks in this format. An appendix on 'Mathematics for Managers' which includes the topics of Matrix Algebra and Differential Calculus. New solved and unsolved problems.
A comprehensive, class-tested text covering all aspects of operations research/management science. Designed for students pursuing business careers requiring managerial ability and decision-making skills, it strongly emphasizes applications through numerous real-life examples and illustrations, chapter outlines, discussion questions, problem sets, and ``application reviews'' which describe scenarios involving actual companies that have benefited from each method discussed. The material is presented in a concise, straightforward manner at a suitable mathematical level, i.e., that of finite mathematics and basic algebra. The mathematical foundation for each quantitative method is clearly set forth and illustrated by means of examples. Appendixes contain brief reviews of calculus and matrix algebra. In addition, the text describes how to apply several well-known and readily available microcomputer software packages to operations research/management science problems. Also includes end-of-chapter glossaries, lists of references, tables, and diagrams.
This book has been developed with a focus on the need to demystify the subject and make it easy for students to grasp the principles and details involved, and make it easily understandable to beginners exposed to the subject for the first time. An attempt has been made to explain things in a logical progression, in the simplest possible way so that neophytes may quickly grasp the concepts and methodology. A novel approach in the book is the illustrative use of computers with TORA package, as a problem-solving tool. In actual practice, situations arise with large and complex problems that are difficult to solve. At such times, using computers to solve problems gives fast and more accurate results. The chapters are arranged so as to progressively explain the workings of various models in actual practice through step-by-step procedures that so simplify and solve them, that even students from a non-mathematics academic background will grasp them quickly. Linear programming, the most powerful tool for managerial decision-making is covered elaborately, including thorough discussion of various LP methods and LP solutions, Duality in LP problems, sensitivity analysis, etc. Models in the book also use Linear Programming to reach solutions including those relating to transportation and transshipment, assignment, and Game Theory&illustrated with screen-shots of a computer with a TORA package. Readers whether students, business executives, managers, researchers and academicians will find that the insights and knowledge obtained from the book will stand them in good stead in both academic as well as occupational pursuits.
Were you looking for the book with access to MyLab Math Global? This product is the book alone and does NOT come with access to MyLab Math Global. Students, if MyLab Math Global is a recommended/mandatory component of the course, please ask your instructor for the correct ISBN and course ID. MyLab Math Global should only be purchased when required by an instructor. Instructors, contact your Pearson representative for more information. There's no doubt that a manager's job is getting tougher. Do it better, do it faster, do it cheaper are the pressures every manager faces. And at the heart of every manager's job is decision-making: deciding what to do and how to do it. This well-respected text looks at how quantitative analysis techniques can be used effectively to support such decision making. As a manager, developing a good understanding of the quantitative analysis techniques at your disposal is crucial. Knowing how, and when, to use them and what their results really mean can be the difference between making a good or bad decision and, ultimately, between business success and failure. Appealing both to students on introductory-level courses and to MBA and postgraduate students, this internationally successful text provides an accessible introduction to a subject area that students often find difficult. Quantitative Analysis for Decision Makers (formerly known as Quantitative Methods for Decision Makers) helps students to understand the relevance of quantitative methods of analysis to management decision-making by relating techniques directly to real-life business decisions in public and private sector organisations and focuses on developing appropriate skills and understanding of how the techniques fit into the wider management process. Key features: The use of real data sets to show how analytical techniques are used in practice “QADM in Action” case studies illustrating how organisations benefit from the use of analytical techniques Articles from the Financial Times illustrating the use of such techniques in a variety of business settings Fully worked examples and exercises supported by Excel data sets Student Progress Check activities in each chapter with solutions A 300+ page Tutors Solutions Manual
This book is specially designed for a course in Quantitative Techniques taught to MBA students. It provides the students with a thorough introduction to basic quantitative tools required to perform analytical evaluations and arrive at logical decisions. The second edition of the book essentially retains the flavour of the first edition. Concepts have been explained in an easy to understand language and emphasis is on practical applications rather than rigorous mathematical treatment. As far as possible, detailed proofs and axioms associated with pure mathematics have been avoided. The text in the second edition has been suitably modified for giving better clarity. Nearly fifty solved examples have been added to various chapters to enable students to understand the nuances of problem solving. Fifty unsolved problems have also been added to give ample scope to the student for practice. The book also includes chapters on transportation models, assignment models and network analysis. KEY FEATURES : Learning objectives at the beginning of each chapter enable students to focus on important points of a chapter. Case studies and real life problems to connect students to the real-world situations. Worked examples to enhance student comprehension of the subject. Numerous well-balanced chapter-end exercises with answers to help students attain confidence and master the concepts. Illustrations on solutions to problems with the help of computer software. Summary at the end of each chapter to help students review the key concepts.
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.
Everybody has to make decisions—they are unavoidable. Yet we receive little or no education or training on how to make decisions. Business decisions can be dif_ cult: which people to hire, which product lines or facilities to expand and which to sell or shut down, which bid or proposal to accept, which process to implement, how much R&D to invest in, which environmental projects should receive the highest priority, etc. This book gives you all the tools you need to... • clarify and reach alignment on goals and objectives and understand trade-offs in reaching those goals, • develop and examine alternatives, • systematically analyze the effects of risk and uncertainty, and • maximize the chances of achieving your goals and objectives. Success (getting what you want) depends on luck and good decision making. You can’t control your luck, but you can maximize your odds by making the best possible decisions, and this book gets you there. Broadly speaking, this book organizes and presents otherwise formal decision-making tools in an intuitively understandable fashion. The presentation is informal, but the concepts and tools are research-based and formally accepted.