Includes bibliographical references (p. 633-634) and index.

Preface. About the Authors. CHAPTER 1 Introduction. Probability Versus Statistics. Overview of the Book. PART ONE Descriptive Statistics. CHAPTER 2 Basic Data Analysis. Data Types. Frequency Distributions. Empirical Cumulative Frequency Distribution. Data Classes. Cumulative Frequency Distributions. Concepts Explained in this Chapter (In Order of Presentation). CHAPTER 3 Measures of Location and Spread. Parameters versus Statistics. Center and Location. Variation. Measures of the Linear Transformation. Summary of Measures. Concepts Explained in this Chapter (In Order of Presentation). CHAPTER 4 Graphical Representation of Data. Pie Charts. Bar Chart. Stem and Leaf Diagram. Frequency Histogram. Ogive Diagrams. Box Plot. QQ Plot. Concepts Explained in this Chapter (In Order of Presentation). CHAPTER 5 Multivariate Variables and Distributions. Data Tables and Frequencies. Class Data and Histograms. Marginal Distributions. Graphical Representation. Conditional Distribution. Conditional Parameters and Statistics. Independence. Covariance. Correlation. Contingency Coefficient. Concepts Explained in this Chapter (In Order of Presentation). CHAPTER 6 Introduction to Regression Analysis. The Role of Correlation. Regression Model: Linear Functional Relationship Between Two Variables. Distributional Assumptions of the Regression Model. Estimating the Regression Model. Goodness of Fit of the Model. Linear Regression of Some Non-Linear Relationship. Two Applications in Finance. Concepts Explained in this Chapter (In Order of Presentation). CHAPTER 7 Introduction to Time Series Analysis. What Is Time Series? Decomposition of Time Series. Representation of Time Series with Difference Equations. Application: The Price Process. Concepts Explained in this Chapter (In Order of Presentation). PART TWO Basic Probability Theory. CHAPTER 8 Concepts of Probability Theory. Historical Development of Alternative Approaches to Probability. Set Operations and Preliminaries. Probability Measure. Random Variable. Concepts Explained in this Chapter (In Order of Presentation). CHAPTER 9 Discrete Probability Distributions. Discrete Law. Bernoulli Distribution. Binomial Distribution. Hypergeometric Distribution. Multinomial Distribution. Poisson Distribution Discrete Uniform Distribution. Concepts Explained in this Chapter (In Order of Presentation). CHAPTER 10 Continuous Probability Distributions. Continuous Probability Distribution Described. Distribution Function. Density Function. Continuous Random Variable. Computing Probabilities from the Density Function. Location Parameters. Dispersion Parameters. Concepts Explained in this Chapter (In Order of Presentation). CHAPTER 11 Continuous Probability Distributions with Appealing Statistical Properties. Normal Distribution. Chi-Square Distribution. Student's t -Distribution. F -Distribution. Exponential Distribution. Rectangular Distribution. Gamma Distribution. Beta Distribution. Log-Normal Distribution. Concepts Explained in this Chapter (In Order of Presentation). CHAPTER 12 Continuous Probability Distributions Dealing with Extreme Events. Generalized Extreme Value Distribution. Generalized Pareto Distribution. Normal Inverse Gaussian Distribution. a-Stable Distribution. Concepts Explained in this Chapter (In Order of Presentation). CHAPTER 13 Parameters of Location and Scale of Random Variables. Parameters of Location. Parameters of Scale. Concepts Explained in this Chapter (In Order of Presentation). Appendix: Parameters for Various Distribution Functions. CHAPTER 14 Joint Probability Distributions. Higher Dimensional Random Variables. Joint Probability Distribution. Marginal Distributions. Dependence. Covariance and Correlation. Selection of Multivariate Distributions. Concepts Explained in this Chapter (In Order of Presentation). CHAPTER 15 Conditional Probability and Bayes' Rule. Conditional Probability. Independent Events. Multiplicative Rule of Probability. Bayes