ISBN-10:
1119220971
ISBN-13:
9781119220978
Pub. Date:
08/01/2016
Publisher:
Wiley
Introduction to Quantitative Methods in Business: With Applications Using Microsoft Office Excel / Edition 1

Introduction to Quantitative Methods in Business: With Applications Using Microsoft Office Excel / Edition 1

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Product Details

ISBN-13: 9781119220978
Publisher: Wiley
Publication date: 08/01/2016
Pages: 320
Product dimensions: 7.20(w) x 10.10(h) x 0.90(d)

About the Author

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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Table of Contents

Preface xiii

About the Companion Website xvii

1 The Mathematical Toolbox 1

1.1 Introduction 1

1.2 Linear Functions 2

1.3 Solving a Simple Linear Equation for One Unknown Variable 3

1.3.1 Solving Two Simultaneous Linear Equations for Two Unknown Variables 4

1.4 Summation Notation 6

1.5 Sets 12

1.5.1 Subset, Empty Set, Universal Set, and Complement of A Set 13

1.5.2 Intersection and Union 14

1.6 Functions and Graphs 15

1.6.1 Vertical Line Test 16

1.7 Working with Functions 17

1.7.1 Evaluating Functions 17

1.7.2 Graphing Functions 18

1.8 Differentiation and Integration 22

1.8.1 Derivative 22

1.8.2 Derivatives of Logarithmic and Exponential Functions 26

1.8.3 Higher Order Derivatives 26

1.8.4 Integration 28

1.8.5 The Definite Integral 29

1.8.6 Some Rules of Integration 31

1.9 Excel Applications 34

Chapter 1 Review 40

Exercises 41

Excel Applications 45

Appendix 1.A A Review of Basic Mathematics 45

1.A.1 Order of Arithmetic Operations 45

1.A.2 Exponents 46

1.A.3 Logarithms 48

1.A.4 Prime Factorization 50

1.A.5 Factoring 51

1.A.6 Fractions: Ratios 52

1.A.6.1 Greatest Common Factor 52

1.A.6.2 Least Common Multiple 52

1.A.6.3 Addition and Subtraction of Fractions 53

1.A.6.4 Multiplication and Division of Fractions 54

1.A.6.5 Mixed Fractions 55

1.A.7 Decimals 56

1.A.7.1 Operations with Decimals 56

1.A.8 Percent 57

1.A.8.1 Finding Percent (%) of a Number 58

1.A.8.2 Finding Percentage Increase (+) or Percentage Decrease (-) 59

1.A.9 Conversions between Decimals (D), Fractions (F), and Percents (P) 60

1.A.9.1 Changing Decimals to Fractions (D → F) 60

1.A.9.2 Changing Fraction to Decimals: (F → D) 60

1.A.9.3 Changing Decimals to Percents (D → P) 60

1.A.9.4 Changing Percents to Decimals (P → D) 61

1.A.9.5 Changing Fractions to Percents (F → P) 61

1.A.9.6 Changing Percents to Fractions (P → F) 62

1.A.10 Ratio and Proportion 62

Exercises 63

2 Applications of Linear and Nonlinear Functions 66

2.1 Introduction 66

2.2 Linear Demand and Supply Functions 66

2.3 Linear Total Cost and Total Revenue Functions 69

2.4 Market Equilibrium 71

2.5 Graphical Presentation of Equilibrium 72

2.6 Applications of Nonlinear Functions 73

2.7 Present Value of an Income Stream 78

2.8 Average Values 79

2.9 Marginal Values 80

2.10 Elasticity 81

2.11 Some Additional Business Applications 84

2.12 Excel Applications 84

Chapter 2 Review 86

Exercises 87

Excel Applications 90

3 Optimization 91

3.1 Introduction 91

3.2 Unconstrained Optimization 91

3.2.1 Models of Profit and Revenue Maximization 91

3.2.2 Solution by Trial and Error (Approximate) Method 92

3.2.3 Solution Using the Calculus Approach 93

3.2.4 Solution by Trial and Error (Approximate) Method 96

3.2.5 Solution Using the Calculus Approach 97

3.3 Models of Cost Minimization: Inventory Cost Functions and EOQ 99

3.3.1 Solution by Trial and Error Method 101

3.3.2 Solution Using the Calculus Approach 103

3.4 Constrained Optimization: Linear Programming 105

3.4.1 Linear Programming: Maximization 106

3.4.1.1 Solution by Graphical Method: First Approach 106

3.4.1.2 Solution by Graphical Method: Second Approach 109

3.4.2 Linear Programming: Minimization 114

3.5 Excel Applications 121

Chapter 3 Review 125

Chapter 3 Eercises 126

Excel Applications 130

4 What Is Business Statistics? 131

4.1 Introduction 131

4.2 Data Description 132

4.2.1 Some Important Concepts in Statistics 132

4.2.2 Scales of Data Measurement 132

4.3 Descriptive Statistics: Tabular and Graphical Techniques 134

4.4 Descriptive Statistics: Numerical Measures of Central Tendency or Location of Data 144

4.4.1 Population Mean 144

4.4.2 Sample Mean 145

4.4.3 Weighted Mean 147

4.4.4 Mean of a Frequency Distribution: Grouped Data 148

4.4.5 Geometric Mean 149

4.4.6 Median 151

4.4.7 Quantiles, Quartiles, Deciles, and Percentiles 152

4.4.8 Mode 153

4.5 Descriptive Statistics: Measures of Dispersion-Variability or Spread 155

4.5.1 Range 155

4.5.2 Variance 155

4.5.3 Standard Deviation 158

4.5.4 Coefficient of Variation 160

4.5.5 Some Important Uses of the Standard Deviation 163

4.5.6 Empirical Rule 165

4.6 Measuring Skewness 166

4.7 Excel Applications 169

Chapter 4 Review 186

Exercises 188

Excel Applications 191

5 Probability and Applications 194

5.1 Introduction 194

5.2 Some Useful Definitions 195

5.3 Probability Sources 196

5.3.1 Objective Probability 196

5.3.2 Subjective Probability 196

5.4 Some Useful Definitions Involving Sets of Events in the Sample Space 197

5.4.1 Complement of a Given Set A 199

5.4.2 Mutually Exclusive Events 200

5.5 Probability Laws 200

5.5.1 General Rule of Addition 200

5.5.2 Rule of Complements 202

5.5.3 Conditional Probability 202

5.5.4 General Rule of Multiplication (Product Rule) 203

5.5.5 Independent Events 204

5.5.6 Probability Tree Approach 204

5.6 Contingency Table 208

5.7 Excel Applications 213

Chapter 5 Review 214

Exercises 215

Excel Applications 218

6 Random Variables and Probability Distributions 219

6.1 Introduction 219

6.2 Probability Distribution of a Discrete Random Variable X 220

6.3 Expected Value, Variance, and Standard Deviation of a Discrete Random Variable X 222

6.3.1 Some Basic Rules of Expectation 224

6.3.2 Some Useful Properties of Variance of X 225

6.3.3 Applications of Expected Values 225

6.4 Continuous Random Variables and Their Probability Distributions 230

6.5 A Specific Discrete Probability Distribution: The Binomial Case 232

6.5.1 Binomial Probability Distribution 232

6.5.2 Mean and Standard Deviation of the Binomial Random Variable 237

6.5.3 Cumulative Binomial Probability Distribution 238

6.6 Excel Applications 241

Chapter 6 Review 245

Exercises 245

Appendix 6. A 252

Table 6.A.1 Binomial Probabilities (X is b(X; n, p)) 252

Table 6.A.2 Cumulative Distribution Function Values for the Binomial Distribution (X is b(X; n, p)) 258

Solutions to Odd-Numbered Exercises 263

Index 291

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