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Herausgeber: John Wiley & Sons
Kategorie: Wissenschaft und neue Technologien
Sprache: Englisch

Beschreibung

A well-balanced and accessible introduction to the elementary quantitative methods and Microsoft® Office Excel® applications used to guide business decision making

Featuring quantitative techniques essential for modeling modern business situations, Introduction to Quantitative Methods in Business: With Applications Using Microsoft® Office Excel® provides guidance to assessing real-world data sets using Excel. The book presents a balanced approach to the mathematical tools and techniques with applications used in the areas of business, finance, economics, marketing, and operations.

The authors begin by establishing a solid foundation of basic mathematics and statistics before moving on to more advanced concepts. The first part of the book starts by developing basic quantitative techniques such as arithmetic operations, functions and graphs, and elementary differentiations (rates of change), and integration. After a review of these techniques, the second part details both linear and nonlinear models of business activity. Extensively classroom-tested, Introduction to Quantitative Methods in Business: With Applications Using Microsoft® Office Excel® also includes:

Numerous examples and practice problems that emphasize real-world business quantitative techniques and applications

Excel-based computer software routines that explore calculations for an assortment of tasks, including graphing, formula usage, solving equations, and data analysis

End-of-chapter sections detailing the Excel applications and techniques used to address data and solutions using large data sets

A companion website that includes chapter summaries, Excel data sets, sample exams and quizzes, lecture slides, and an Instructors’ Solutions Manual

Introduction to Quantitative Methods in Business: With Applications Using Microsoft® Office Excel® is an excellent textbook for undergraduate-level courses on quantitative methods in business, economics, finance, marketing, operations, and statistics. The book is also an ideal reference for readers with little or no quantitative background who require a better understanding of basic mathematical and statistical concepts used in economics and business.

Bharat Kolluri, Ph.D., is Professor of Economics in the Department of Economics, Finance, and Insurance at the University of Hartford. A member of the American Economics Association, his research interests include econometrics, business statistics, quantitative decision making, applied macroeconomics, applied microeconomics, and corporate finance.

Michael J. Panik, Ph.D., is Professor Emeritus in the Department of Economics, Finance, and Insurance at the University of Hartford. He has served as a consultant to the Connecticut Department of Motor Vehicles as well as to a variety of health care organizations. In addition, Dr. Panik is the author of numerous books, including Growth Curve Modeling: Theory and Applications and Statistical Inference: A Short Course, both published by Wiley.

Rao N. Singamsetti, Ph.D., is Associate Professor in the Department of Economics, Finance, and Insurance at the University of Hartford. A member of the American Economics Association, his research interests include the status of war on poverty in the United States since the 1960s and forecasting foreign exchange rates using econometric methods.

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Leseprobe

Cover

Title Page

Dedication

Preface

About the Companion Website

Chapter 1: The Mathematical Toolbox

1.1 Introduction

1.2 Linear Functions

1.3 Solving A Simple Linear Equation for One Unknown Variable

1.4 Summation Notation

1.5 Sets

1.6 Functions and Graphs

1.7 Working with Functions

1.8 Differentiation and Integration

1.9 Excel Applications

Chapter 1 Review

Exercises

Excel Applications

Appendix 1.A: A Review of Basic Mathematics

Exercises

Chapter 2: Applications of Linear and Nonlinear Functions

2.1 Introduction

2.2 Linear Demand and Supply Functions

2.3 Linear Total Cost and Total Revenue Functions

2.4 Market Equilibrium

2.5 Graphical Presentation of Equilibrium

2.6 Applications of Nonlinear Functions

2.7 Present Value of an Income Stream

2.8 Average Values

2.9 Marginal Values

2.10 Elasticity

2.11 Some Additional Business Applications

2.12 Excel Applications

Chapter 2 Review

Exercises

Excel Applications

Chapter 3: Optimization

3.1 Introduction

3.2 Unconstrained Optimization

3.3 Models of Cost Minimization: Inventory Cost Functions and EOQ

3.4 Constrained Optimization: Linear Programming

3.5 Excel Applications

Chapter 3 Review

Chapter 3 Exercises

Excel Applications

Chapter 4: What Is Business Statistics?

4.1 Introduction

4.2 Data Description

4.3 Descriptive Statistics: Tabular and Graphical Techniques

4.4 Descriptive Statistics: Numerical Measures of Central Tendency or Location of Data

4.5 Descriptive Statistics: Measures of Dispersion—Variability or Spread

4.6 Measuring Skewness

4.7 Excel Applications

Chapter 4 Review

Exercises

Excel Applications

Chapter 5: Probability and Applications

5.1 Introduction

5.2 Some Useful Definitions

5.3 Probability Sources

5.4 Some Useful Definitions Involving Sets of Events in the Sample Space

5.5 Probability Laws

5.6 Contingency Table

5.7 Excel Applications

Chapter 5 Review

Exercises

Excel Applications

Chapter 6: Random Variables and Probability Distributions

6.1 Introduction

6.2 Probability Distribution of A Discrete Random Variable X

6.3 Expected Value, Variance, and Standard Deviation of A Discrete Random Variable X

6.4 Continuous Random Variables and Their Probability Distributions

6.5 A Specific Discrete Probability Distribution: The Binomial Case

6.6 Excel Applications

Chapter 6 Review

Exercises

Appendix 6.A

Solutions to Odd-Numbered Exercises

Index

End User License Agreement

List of Tables

Table 1.1a

Table 1.1b

Table 1.2

Table 1.3

Table 1.4

Table 1.5

Table 1.6

Table A.1

Table 2.1a

Table 2.1b

Table 2.2

Table 2.3

Table 2.4

Table 3.1

Table 3.2

Table 3.3

Table 3.4

Table 3.5

Table 3.6

Table 3.7

Table 3.8

Table 3.9

Table 3.10

Table 3.11

Table 3.12

Table 4.1

Table 4.2

Table 4.3a

Table 4.3b

Table 4.3c

Table 4.4

Table 4.5

Table 4.6a

Table 4.6b

Table 4.6c

Table 4.6d

Table 4.7

Table 4.8

Table 4.9a

Table 4.9b

Table 4.10

Table 4.11a

Table 4.11b

Table 4.12

Table 4.13a

Table 4.13b

Table 4.13c

Table 4.13d

Table 4.14

Table 4.15

Table 4.16

Table 5.1

Table 5.2

Table 5.3

Table 6.1a

Table 6.1b

Table 6.2

Table 6.3

Table 6.4a

Table 6.4b

Table 6.5a

Table 6.5b

Table 6.6a

Table 6.6b

Table 6.7

Table 6.8a

Table 6.8b

Table 6.8c

Table 6.8d

Table 6.9a

Table 6.9b

Table 6.10

Table 6.11

Table 6.12

Table 6.13

Table 6.A.1

Table 6.A.2

Table 4.3b

Table 4.3c

Table 4.4

Table 4.8b

Table 4.8c

Table 4.8d

Table 6.12

List of Illustrations

Figure 1.1

Figure 1.2

Figure 1.3

Figure 1.4

Figure 1.6

Figure 1.7

Figure 1.8

Figure 1.5

Figure 1.9

Figure 1.10

Figure A.1

Figure A.2

Figure 2.1

Figure 2.2

Figure 2.3

Figure 2.4

Figure 2.5

Figure 2.6

Figure 3.1

Figure 3.2

Figure 3.3

Figure 3.4

Figure 3.5

Figure 3-6

Figure 3.7

Figure 3.8

Figure 3.9

Figure 3.10

Figure 3.11

Figure 3.12

Figure 3.13

Figure 3.14

Figure 3.15

Figure 3.16

Figure 3.17

Figure 3.18

Figure 4.1

Figure 4.2

Figure 4.3

Figure 4.4

Figure 4.5

Figure 4.6

Figure 4.7

Figure 4.8

Figure 4.9

Figure 4.10

Figure 5.1

Figure 5.2

Figure 5.3

Figure 5.4

Figure 5.5

Figure 5.6

Figure 5.7

Figure 5.8

Figure 5.9

Figure 5.10

Figure 5.11

Figure 6.1

Figure 6.2

Figure 6.3

Figure 6.4

Figure 4.1

Figure 4.3

Figure 4.4

Figure 4.9

Figure 4.11

Figure 4.12

Guide

Cover

Table of Contents

Begin Reading

Chapter 1

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Introduction to Quantitative Methods in Business With Applications Using Microsoft® Office Excel®

Bharat Kolluri

Michael J. Panik

Rao Singamsetti

Barney School of BusinessUniversity of Hartford

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

No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, scanning, or otherwise, except as permitted under Section 107 or 108 of the 1976 United States Copyright Act, without either the prior written permission of the Publisher, or authorization through payment of the appropriate per-copy fee to the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, (978) 750–8400, fax (978) 750–4470, or on the web at www.copyright.com. Requests to the Publisher for permission should be addressed to the Permissions Department, John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, (201) 748–6011, fax (201) 748–6008, or online at http://www.wiley.com/go/permission.

Limit of Liability/Disclaimer of Warranty: While the publisher and author have used their best efforts in preparing this book, they make no representations or warranties with respect to the accuracy or completeness of the contents of this book and specifically disclaim any implied warranties of merchantability or fitness for a particular purpose. No warranty may be created or extended by sales representatives or written sales materials. The advice and strategies contained herein may not be suitable for your situation. You should consult with a professional where appropriate. Neither the publisher nor author shall be liable for any loss of profit or any other commercial damages, including but not limited to special, incidental, consequential, or other damages.

For general information on our other products and services or for technical support, please contact our Customer Care Department within the United States at (800) 762–2974, outside the United States at (317) 572–3993 or fax (317) 572–4002.

Wiley also publishes its books in a variety of electronic formats. Some content that appears in print may not be available in electronic formats. For more information about Wiley products, visit our web site at www.wiley.com.

Library of Congress Cataloging-in-Publication Data

Names: Kolluri, Bharat, author. | Panik, Michael J., author. | Singamsetti, Rao, author.

Title: Introduction to quantitative methods in business : with applications using Microsoft Office Excel / Bharat Kolluri, Michael J. Panik, Rao Singamsetti.

Description: Hoboken, New Jersey : John Wiley & Sons, Inc., [2017] | Includes index.

Identifiers: LCCN 2016017312 | ISBN 9781119220978 (cloth) | ISBN 9781119220992 (epub)

Subjects: LCSH: Business mathematics. | Management--Mathematical models. | Microsoft Excel (Computer file)

Classification: LCC HF5691 .K71235 2017 | DDC 650.0285/54--dc23 LC record available at https://lccn.loc.gov/2016017312

ISBN:9781119220978

Dedication

To our WivesVijaya, Paula, and Andal

Preface

A proper understanding of Economics as well as Business disciplines, such as Finance, Marketing, and Operations, requires a basic knowledge of linear and nonlinear relationships and, in general, the fundamental techniques of quantitative methods. The following techniques are some of the examples:

Basic optimization:

Businesses are, for the most part, typically trying to maximize or minimize something. And that “something” is usually depicted by an equation that is or is not subject to side conditions or constraints.

Basic statistical methods:

Acquiring an understanding of descriptive statistical tools for presenting and analyzing data is crucial for making sound business decisions under uncertainty.

Indeed, a student's ability to model a business situation and apply these quantitative techniques via Microsoft® Office Excel® and other computer software has to be an essential component of any modern business curriculum. In this book, we have incorporated Excel as a tool for problem solving. We have included specific instructions for the usage of Excel Add-ins in selected chapter examples and exercises. For the most part, there are not many texts that adequately deal with these techniques at a beginning or foundational level. To rectify this deficiency, we start first with principles – we develop a solid foundation in arithmetic operations, functions and graphs, and elementary differentiation (rates of change) and integration. Once this foundation is built, we then develop both linear and nonlinear models of business activity and their solutions. And, at all times, the meaning of the solution is fully discussed.

The intended audience includes students enrolled in undergraduate courses in business programs proper, or even in pre-MBA programs, who need a review of, or first exposure to, the basics of mathematics and statistics so that they can move on to the more advanced courses in their curriculum. In this regard, our objective is to close the skills gap that many students have in the quantitative area.

This textbook has many strengths:

Getting students to think in terms of modeling business activity.

An applications orientation.

Fully classroom tested.

Starts with basic mathematics and offers more advanced concepts once a solid grounding in fundamentals is attained.

Students do not get “bogged down” in tedious calculations since the accompanying computer routines perform the “heavy lifting.”

A supplemental Web site contains data sets, lecture slides, sample exams, and quizzes.

In fact, the aforementioned (Excel-based) computer software enable students to perform an assortment of tasks such as graphing, formulas usage, solving equations, and data analysis. More specifically, these are

copy and paste,

filling a range: the Fill handle,

entering a formula,

copying formulas,

absolute versus relative cell addresses,

common error messages, and

decisions and optimization (solving simultaneous equations and linear programming problems) using the ‘Solver’ Add-in program.

In this text, each quantitative technique is illustrated with many examples that are fully solved and that are accompanied by a variety of practice problems emphasizing business applications and designed to gauge the student's understanding of the concepts involved. Given the nature of the subject matter, the text is organized into six chapters, with the first three chapters dealing with the use of mathematical modeling and quantitative techniques in business. The next three chapters deal with business applications of descriptive statistics, probability, and probability distributions.

In terms of topics covered, this text is not at all encyclopedic and, with respect to its size, is quite manageable and should not intimidate or overwhelm students. Our objective is to simply do a few things well and to provide a semester's worth of material that can readily be taught at a reasonable and unhurried pace.

Chapter 1 reviews the basic mathematical concepts and methods with business applications. Chapter 2 deals with linear and nonlinear applications of quantitative techniques in business. Optimization techniques, both unconstrained and constrained, are presented in Chapter 3. Chapter 4 covers descriptive statistics, including measures of location and variability. Chapter 5 includes probability, probability distribution, rules of probability, and contingency table applications. Finally, Chapter 6 introduces both discrete and continuous random variables, expected values, and decision making with payoff tables, and presents general types of distributions such as the binomial distribution and its applications. Throughout the text, special emphasis is placed upon providing many examples that deal with real data. Abbreviated solutions to odd-numbered exercises are presented at the end of the textbook.

Why such an emphasis on “tools?” For those who follow employment issues, it has been estimated that the typical worker/professional will hold an average of seven jobs during his/her working career – and at this point in time, at least half of those jobs have not been even invented yet. The moral of this point is that students need, in terms of their skill set, to be flexible and nimble. Clearly, a firm grounding in analytical tools makes one highly trainable and adaptable. To build any modern “skills edifice,” one needs a solid foundation.

But this is only part of the story. In the latest issue of Economic Letter (Vol. 9, No. 5, May 2014) published by the Dallas Federal Reserve Bank, it was mentioned that “the number of people performing low-skill, low-pay manual labor tasks has grown with the number undertaking high-skill, high-pay, non-routine principally problem-solving jobs.” Middle-skill jobs have been lost in this U.S. labor market polarization or hollowing-out. It is the cognitive nonroutine jobs that are high-skilled jobs that require performing abstract tasks such as problem solving, intuition, and persuasion – jobs that typically require a college degree and some analytical expertise. Let us face it, the high-skill, high-pay jobs will not be landed by the innumerate.

Our sincere thanks go to our colleagues, Profs. Jim Peta and Frank Dellolacono at the University of Hartford, for their support and encouragement. A special note of thanks goes to our office coordinator, Alice Schoenrock, and to our graduate assistant, Lavanya Raghavan, for their timely typing of the various sections and revisions of the text. We are also grateful to our previous graduate assistant, Mustafa Atalay, for helping with the preparation of examples and solutions.

We also acknowledge the support and encouragement of Susanne Steitz-Filler, Senior Editor, Mathematics and Statistics; Allison McGinniss, Project Editor; and Sari Friedman, Editorial Program Coordinator, at John Wiley & Sons, Inc.

Bharat Kolluri

Michael Panik

Rao Singamsetti

About the Companion Website

This book is accompanied by a companion website:

www.wiley.com/go/Kolluri/QuantitativeMethods

The Instructor's website includes:

Instructor's Solutions Manual

Sample exams and quizzes

Lecture slides

Excel data sets

Supplementary exercises

Chapter summaries

The Student's website includes:

Chapter summaries

Excel data sets

Supplementary exercises

Sample exams and quizzes with questions only

Chapter 1The Mathematical Toolbox

1.1 Introduction

This chapter is essentially about applicable analytical tools. We cover items such as linear equations, simultaneous linear equations (involving two equations in two unknowns), the summation operator, sets (and set operations), general functions and graphs, and a brief exposure to differentiation and integration.

Our experience has indicated that some students might benefit from a review of the basic mathematical concepts typically studied in high school mathematics classes or in courses that might be offered in the first year of college. This is why we have included an optional appendix at the end of this chapter for those students in need of a refresher in topics such as exponents, factoring, fractions, and decimals and percents, among others. This review provides the student with a firm grounding in the fundamental mathematical tools needed for problem solving. Indeed, these basic foundation skills in elementary mathematics are necessary for developing and effecting business applications. For instance, derivatives of functions are not calculated for their own sake. One usually has to simplify a derivative in order for it to be useful in, say, determining the maximum of a profit function or the minimum of a cost function. While many students can readily apply the rules of differentiation, they often lack the algebraic skills required to simplify a derivative. (This is why some students describe the calculus as “too difficult.”) The appendix to this chapter attempts to overcome this difficulty.

As to the approach followed throughout this text, and within this chapter proper, a few key notions have motivated our thinking. First, we want students to think in terms of the modeling of business activity. To this end, operating in terms of functions is critical. That is, any decision maker must identify those variables (called independent or decision variables) that are under his/her control. Once such variables are recognized and manipulated, other variables (called response variables) typically react in a deterministic and predictable fashion.

For instance, suppose a manager wants to increase the sales of some consumer product. What, if anything, can be done to facilitate an increase in sales revenue? What sort of decision variable can a manager manipulate? How about increasing the organizations advertising budget? Generally, firms advertise to increase sales (and/or to maintain market share). Thus, advertising expenditure is the decision or control variable and sales level is the response variable.

What might a revenue response look like? Possibly, the relationship between advertising (X) and sales revenue (Y) is one of direct proportionality (e.g., a dollar increase in advertising expenditure might always precipitate, say, 3 dollars in sales revenue), or maybe the advertising response increases at an increasing rate. Obviously, we are describing, in the first case, a linear relationship between advertising and revenue, and, in the second instance, a nonlinear one. Each is an example of a functional relationship between these two variables, which is of the general form Y = f(X). For the linear case, structurally,

And for the nonlinear (quadratic) case,

To reiterate, decision makers must think in terms of functions—in terms of relationships between decision variables and response variables.

Second, one might benefit from thinking in terms of sets of items. Here the use of set operations enables us to “create order” by organizing information in a very systematic fashion. This process will prove particularly useful when we introduce uncertainty into the decision-making picture and work with probability calculations.

To consider an additional decision-making theme/approach, let us return to the nonlinear advertising expenditure versus sales revenue relationship posited earlier. Specifically, how does one know if, at a particular advertising level, sales revenue is actually increasing at an increasing rate? To answer this question, we can employ a very useful and versatile analytical device, namely the requisite derivatives of a function at a given point—but more on this calculus approach later on.

1.2 Linear Functions

An equation like is known as a linear function. Here, is called the slope of the linear function; it measures the change in the value of the dependent variable as a result of a one unit change in the value of the independent variable. It is also obtained as the ratio of the change in to the change in . That is, . is also called the coefficient of . is known as the Y-intercept. It measures the value of when . Both and are constants.

Note the following:

A horizontal line has zero slope.

A vertical line has no slope or its slope is undefined.

A line rising from left to right has positive slope.

A line falling from left to right has negative slope.

1.3 Solving A Simple Linear Equation for One Unknown Variable

Finding the particular value of the unknown variable in a linear equation is a useful algebraic exercise. When solving for the unknown variable in a single linear equation, all other values are assumed to be known. For example, let us solve the equation . If we subtract 42 from both sides, the equation will be . Dividing both sides by 6, will be. It is a useful practice to substitute the answer into the original equation so as to check the solution. In our case, is correct, so X = −7 is the solution. Let us say we have the equation, . To solve for X, all other values are assumed to be known. So, and thus .