ABSTRACT
This introduction presents an overview of the key concepts discussed in the subsequent chapters of this book. The book presents an introduction to probability by encompassing algebra of sets, probability space, conditional probability, the law of total probability and independence, Bayes' Rule, and counting methods. It offers an extensive summary of descriptive statistics analysis by presenting statistics for measuring central tendency, variability, shape, and graphical description of data for exploratory data analysis. The book gives the notion of random variables, discrete random variables and continuous random moments, joint random variables distribution, covariance, and other related measures. It presents some valuable discrete and continuous random variable distributions as well as describes the concepts of functions of random variables and Taylor series. The book presents the ideas of data scaling, distance measures, and some classical data clustering methods.
