Solutions Manual to Accompany Introduction to Quantitative Methods in Business: with Applications Using Microsoft Office Excel

Bharat Kolluri, PhD, 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, PhD, 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 healthcare organizations. In addition, Dr. Panik is the author of numerous books including Growth Curve Modeling: Theory and Applicationsand Statistical Inference: A Short Course, both published by Wiley.Rao N. Singamsetti, PhD, 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 1960’s and forecasting foreign exchange rates using econometric methods.

• 1. The Mathematical Toolbox: A Summary 11.2 Linear Functions 11.3.1 Solving Two Simultaneous Linear Equations 11.4 Summation Notation 21.5 Sets 31.6 Functions and Graphs 31.7 Working with Functions 41.8 Differentiation and Integration 5Solutions to Odd-Numbered Exercises 82. Applications of Linear and Nonlinear Functions: A Summary 322.2 Linear Demand and Supply Functions 322.3 Linear Total Cost and Total Revenue Functions 332.4 Market Equilibrium 332.6 Applications of Nonlinear Functions 342.7 Present Value of an Income Stream 352.8 Average Values 352.9 Marginal Values 362.10 Elasticity 36Solutions to Odd-Numbered Exercises 373. Optimization: A Summary 473.2 Unconstrained Optimization 473.2.1 Models of Profit and Revenue Maximization 473.2.3 Solution Using the Calculus Approach 473.2.5 Solution Using the Calculus Approach 473.3 Models of Cost Minimization: Inventory Cost Functions and Economic Order Quantity (EOQ) 483.3.2 Solution Using the Calculus Approach 493.4 Constrained Optimization: Linear Programming 503.4.1 Linear Programming: Maximization 503.4.2 Linear Programming: Minimization 51Solutions to Odd-Numbered Exercises 524. What Is Business Statistics? 684.3 Descriptive Statistics: Tabular and Graphical Techniques 684.4 Descriptive Statistics: Numerical Measures of Central Tendency or Location of Data 704.4.1 Population Mean 704.4.2 Sample Mean 704.4.3 Weighted Mean 704.4.4 Mean of a Frequency Distribution: Grouped Data 714.4.5 Geometric Mean 714.4.6 Median 714.4.7 Quantiles, Quartiles, Deciles, and Percentiles 714.4.8 Mode 724.5 Descriptive Statistics: Measures of Dispersion (Variability or Spread) 734.5.2 Variance 734.5.3 Standard Deviation 744.5.4 Coefficient of Variation 744.5.5 Some Important Uses of the Standard Deviation 751. Standardization of Values 752. Chebysheff’s Theorem 754.5.6 Empirical Rule 754.6 Measuring Skewness 76Solutions to Odd-Numbered Exercises 765. Probability and Applications 965.2 Some Useful Definitions 965.3 Probability Sources 965.3.1 Objective Probability 965.4 Some Useful Definitions Involving Sets of Events in the Sample Space 965.5 Probability Laws 975.5.2 Rule of Complements 975.5.3 Conditional Probability 975.5.4 General Multiplication Rule (Product Rule) 975.5.5 Independent Events 985.5.6 Probability Tree Approach 985.6 Contingency Table 98Solutions to Odd-Numbered Exercises 1006. Random Variables and Probability Distributions 1056.2 Probability Distribution of a Discrete Random Variable X 1056.3 Expected Value, Variance, and Standard Deviation of a Discrete Random Variable 1066.3.1 Some Basic Rules of Expectation 1066.3.2 Some Useful Properties of the Variance of X 1076.4 Continuous Random Variables and Their Probability Distributions 1076.5 A Specific Discrete Probability Distribution: The Binomial Case 1086.5.1 Binomial Probability Distribution 1086.5.2 Mean and Standard Deviation of the Binomial Random Variable 1096.5.3 Cumulative Binomial Probability Distribution 110Solutions to Odd-Numbered Exercises 110Index 119