An Introduction to Probability Theory and Its Applications offers comprehensive explanations to complex statistical problems. Delving deep into densities and distributions while relating critical formulas, processes, and approaches, this rigorous text provides a solid grounding in probability with practice problems throughout. Emphasizing application without neglecting theory, the text carefully explains complex topics and their practical use. This Indian edition enhances the coverage with new and updated content. It introduces new sections discussing nonnormal densities in higher dimensions, statement of H?jek-R?nyi inequality, and Kolmogorov's strong law of large numbers. Additionally, a new appendix , featuring simplified real-world examples using R software, has been added. Many end-of-chapter problems throughout the book are new or revised. It also includes multiple-choice questions derived from various competitive examinations.