Probability and Statistics is a structured and student-friendly textbook that provides a deep exploration of fundamental and advanced concepts in probability theory and statistical analysis. Designed to serve a broad audience, including undergraduate and postgraduate students across mathematics, engineering, computer science, and applied sciences, this book offers both clarity and rigor in its approach.

The content spans a wide range of topics beginning with foundational definitions of probability—classical, statistical, and axiomatic—and progresses into the study of random variables, moment-generating functions, and core probability theorems. It thoroughly explores discrete and continuous probability distributions, such as Binomial, Poisson, and Normal, making it ideal for both theoretical understanding and practical application.

Further sections delve into descriptive statistics, measures of central tendency and dispersion, correlation, regression, and multivariate analysis. A dedicated chapter on hypothesis testing equips readers with essential tools for making inferences from data, covering t-tests, chi-square tests, F-tests, and large-sample methods. The final part of the book introduces the principles of experimental design, with emphasis on analysis of variance (ANOVA) and factorial experiments—key techniques in statistical research and industrial studies.

Packed with illustrative examples, solved problems, and exercise sets, the book supports self-learning while encouraging analytical thinking. It is especially useful for those preparing for academic exams, research work, and data-driven decision-making in professional environments. This textbook bridges theoretical insights with real-world applications, making it a valuable resource for both classroom learning and independent study.