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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.

Tabla de contenidos provista por Syndetics

• Preface(p. xiii)
• About the Companion Website(p. xvii)
• 1 The Mathematical Toolbox(p. 1)
• 1.1 Introduction(p. 1)
• 1.2 Linear Functions(p. 2)
• 1.3 Solving a Simple Linear Equation for One Unknown Variable(p. 3)
• 1.3.1 Solving Two Simultaneous Linear Equations for Two Unknown Variables(p. 4)
• 1.4 Summation Notation(p. 6)
• 1.5 Sets(p. 12)
• 1.5.1 Subset, Empty Set, Universal Set, and Complement of A Set(p. 13)
• 1.5.2 Intersection and Union(p. 14)
• 1.6 Functions and Graphs(p. 15)
• 1.6.1 Vertical Line Test(p. 16)
• 1.7 Working with Functions(p. 17)
• 1.7.1 Evaluating Functions(p. 17)
• 1.7.2 Graphing Functions(p. 18)
• 1.8 Differentiation and Integration(p. 22)
• 1.8.1 Derivative(p. 22)
• 1.8.2 Derivatives of Logarithmic and Exponential Functions(p. 26)
• 1.8.3 Higher Order Derivatives(p. 26)
• 1.8.4 Integration(p. 28)
• 1.8.5 The Definite Integral(p. 29)
• 1.8.6 Some Rules of Integration(p. 31)
• 1.9 Excel Applications(p. 34)
• Chapter 1 Review(p. 40)
• Exercises(p. 41)
• Excel Applications(p. 45)
• Appendix 1.A(p. 45)
• 1.A.1 Order of Arithmetic Operations(p. 45)
• 1.A.2 Exponents(p. 46)
• 1.A.3 Logarithms(p. 48)
• 1.A.4 Prime Factorization(p. 50)
• 1.A.5 Factoring(p. 51)
• 1.A.6 Fractions: Ratios(p. 52)
• 1.A.6.1 Greatest Common Factor(p. 52)
• 1.A.6.2 Least Common Multiple(p. 52)
• 1.A.6.3 Addition and Subtraction of Fractions(p. 53)
• 1.A.6.4 Multiplication and Division of Fractions(p. 54)
• 1.A.6.5 Mixed Fractions(p. 55)
• 1.A.7 Decimals(p. 56)
• 1.A.7.1 Operations with Decimals(p. 56)
• 1.A.8 Percent(p. 57)
• 1.A.8.1 Finding Percent (%) of a Number(p. 58)
• 1.A.8.2 Finding Percentage Increase (+) or Percentage Decrease (-)(p. 59)
• 1.A.9 Conversions between Decimals (D), Fractions (F), and Percents (P)(p. 60)
• 1.A.9.1 Changing Decimals to Fractions (D → F)(p. 60)
• 1.A.9.2 Changing Fraction to Decimals: (F → D)(p. 60)
• 1.A.9.3 Changing Decimals to Percents (D → P)(p. 60)
• 1.A.9.4 Changing Percents to Decimals (P → D)(p. 61)
• 1.A.9.5 Changing Fractions to Percents (F → P)(p. 61)
• 1.A.9.6 Changing Percents to Fractions (P → F)(p. 62)
• 1.A.10 Ratio and Proportion(p. 62)
• Exercises(p. 63)
• 2 Applications of Linear and Nonlinear Functions(p. 66)
• 2.1 Introduction(p. 66)
• 2.2 Linear Demand and Supply Functions(p. 66)
• 2.3 Linear Total Cost and Total Revenue Functions(p. 69)
• 2.4 Market Equilibrium(p. 71)
• 2.5 Graphical Presentation of Equilibrium(p. 72)
• 2.6 Applications of Nonlinear Functions(p. 73)
• 2.7 Present Value of an Income Stream(p. 78)
• 2.8 Average Values(p. 79)
• 2.9 Marginal Values(p. 80)
• 2.10 Elasticity(p. 81)
• 2.11 Some Additional Business Applications(p. 84)
• 2.12 Excel Applications(p. 84)
• Chapter 2 Review(p. 86)
• Exercises(p. 87)
• Excel Applications(p. 90)
• 3 Optimization(p. 91)
• 3.1 Introduction(p. 91)
• 3.2 Unconstrained Optimization(p. 91)
• 3.2.1 Models of Profit and Revenue Maximization(p. 91)
• 3.2.2 Solution by Trial and Error (Approximate) Method(p. 92)
• 3.2.3 Solution Using the Calculus Approach(p. 93)
• 3.2.4 Solution by Trial and Error (Approximate) Method(p. 96)
• 3.2.5 Solution Using the Calculus Approach(p. 97)
• 3.3 Models of Cost Minimization: Inventory Cost Functions and EOQ(p. 99)
• 3.3.1 Solution by Trial and Error Method(p. 101)
• 3.3.2 Solution Using the Calculus Approach(p. 103)
• 3.4 Constrained Optimization: Linear Programming(p. 105)
• 3.4.1 Linear Programming: Maximization(p. 106)
• 3.4.1.1 Solution by Graphical Method: First Approach(p. 106)
• 3.4.1.2 Solution by Graphical Method: Second Approach(p. 109)
• 3.4.2 Linear Programming: Minimization(p. 114)
• 3.5 Excel Applications(p. 121)
• Chapter 3 Review(p. 125)
• Chapter 3 Eercises(p. 126)
• Excel Applications(p. 130)
• 4 What Is Business Statistics?(p. 131)
• 4.1 Introduction(p. 131)
• 4.2 Data Description(p. 132)
• 4.2.1 Some Important Concepts in Statistics(p. 132)
• 4.2.2 Scales of Data Measurement(p. 132)
• 4.3 Descriptive Statistics: Tabular and Graphical Techniques(p. 134)
• 4.4 Descriptive Statistics: Numerical Measures of Central Tendency or Location of Data(p. 144)
• 4.4.1 Population Mean(p. 144)
• 4.4.2 Sample Mean(p. 145)
• 4.4.3 Weighted Mean(p. 147)
• 4.4.4 Mean of a Frequency Distribution: Grouped Data(p. 148)
• 4.4.5 Geometric Mean(p. 149)
• 4.4.6 Median(p. 151)
• 4.4.7 Quantiles, Quartiles, Deciles, and Percentiles(p. 152)
• 4.4.8 Mode(p. 153)
• 4.5 Descriptive Statistics: Measures of Dispersion-Variability or Spread(p. 155)
• 4.5.1 Range(p. 155)
• 4.5.2 Variance(p. 155)
• 4.5.3 Standard Deviation(p. 158)
• 4.5.4 Coefficient of Variation(p. 160)
• 4.5.5 Some Important Uses of the Standard Deviation(p. 163)
• 4.5.6 Empirical Rule(p. 165)
• 4.6 Measuring Skewness(p. 166)
• 4.7 Excel Applications(p. 169)
• Chapter 4 Review(p. 186)
• Exercises(p. 188)
• Excel Applications(p. 191)
• 5 Probability and Applications(p. 194)
• 5.1 Introduction(p. 194)
• 5.2 Some Useful Definitions(p. 195)
• 5.3 Probability Sources(p. 196)
• 5.3.1 Objective Probability(p. 196)
• 5.3.2 Subjective Probability(p. 196)
• 5.4 Some Useful Definitions Involving Sets of Events in the Sample Space(p. 197)
• 5.4.1 Complement of a Given Set A(p. 199)
• 5.4.2 Mutually Exclusive Events(p. 200)
• 5.5 Probability Laws(p. 200)
• 5.5.1 General Rule of Addition(p. 200)
• 5.5.2 Rule of Complements(p. 202)
• 5.5.3 Conditional Probability(p. 202)
• 5.5.4 General Rule of Multiplication (Product Rule)(p. 203)
• 5.5.5 Independent Events(p. 204)
• 5.5.6 Probability Tree Approach(p. 204)
• 5.6 Contingency Table(p. 208)
• 5.7 Excel Applications(p. 213)
• Chapter 5 Review(p. 214)
• Exercises(p. 215)
• Excel Applications(p. 218)
• 6 Random Variables and Probability Distributions(p. 219)
• 6.1 Introduction(p. 219)
• 6.2 Probability Distribution of a Discrete Random Variable X(p. 220)
• 6.3 Expected Value, Variance, and Standard Deviation of a Discrete Random Variable X(p. 222)
• 6.3.1 Some Basic Rules of Expectation(p. 224)
• 6.3.2 Some Useful Properties of Variance of X(p. 225)
• 6.3.3 Applications of Expected Values(p. 225)
• 6.4 Continuous Random Variables and Their Probability Distributions(p. 230)
• 6.5 A Specific Discrete Probability Distribution: The Binomial Case(p. 232)
• 6.5.1 Binomial Probability Distribution(p. 232)
• 6.5.2 Mean and Standard Deviation of the Binomial Random Variable(p. 237)
• 6.5.3 Cumulative Binomial Probability Distribution(p. 238)
• 6.6 Excel Applications(p. 241)
• Chapter 6 Review(p. 245)
• Exercises(p. 245)
• Appendix 6. A (p. 252)
• Table 6.A.1 Binomial Probabilities (X is b(X; n, p))(p. 252)
• Table 6.A.2 Cumulative Distribution Function Values for the Binomial Distribution (X is b(X; n, p))(p. 258)
• Solutions to Odd-Numbered Exercises(p. 263)
• Index(p. 291)

Notas de autor provistas por Syndetics

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.