A parameterized mathematical function that provides the probabilities of different outcomes for a random variable is referred to as a statistical distribution. These distributions are applied to continuous, discrete, and bivariate random variables. Some of the most prominent statistical distributions are exponential, Erlang, gamma, beta, Weibull, normal, lognormal, left-truncated normal, right-truncated normal, triangular, discrete uniform, binomial, geometric and Pascal. The knowledge of statistical distributions is fundamental for researchers in almost all disciplines. Understanding when and how to apply each of the distributions in research studies, with a goal to identify the distribution that best applies to the study is also crucial. This book traces the progress of this field and highlights some of its key concepts and applications. Some of the diverse topics covered herein address the varied branches that fall under statistical distributions. This book will serve as a reference to a broad spectrum of readers.