The book “Numerical Techniques and Statistical Methods” emerges from the collective efforts of multiple authors and subject experts who sought to create a comprehensive academic resource that bridges theoretical foundations with practical computational applications. Designed primarily for undergraduate and postgraduate students in engineering, science, and applied mathematics, this book aims to strengthen problem-solving capabilities through rigorous yet approachable exposition.
In today’s data-driven and computation-oriented era, understanding numerical and statistical approaches has become indispensable. Numerical techniques serve as the cornerstone for solving mathematical models that are otherwise analytically intractable, while statistical methods enable efficient decision-making, data interpretation, and uncertainty analysis. This book integrates both domains to provide learners with a unified framework that supports analysis, experimentation, and real-world implementation.
The content has been organized systematically to cover essential concepts such as error analysis, numerical solutions of algebraic and transcendental equations, finite difference methods, interpolation, numerical integration, and regression. Likewise, the statistical sections explore probability distributions, hypothesis testing, correlation, regression, and analysis of variance, each complemented with illustrative examples, MATLAB/Python programs, and solved numerical exercises to aid conceptual clarity and independent learning.
The authors have endeavored to strike a balance between theory and computation, ensuring that each chapter begins with fundamental principles and progresses logically toward complex applications. The inclusion of algorithmic representations and practical case studies makes this text suitable not only for classroom teaching but also for self-learning and project-oriented research.
We express our sincere gratitude to our respective institutions, reviewers, and academic peers whose valuable feedback and intellectual contributions enriched this work. We also thank the students and researchers whose curiosity and enthusiasm have been a driving force behind the preparation of this book. It is our hope that this collaborative work serves as a dependable guide and enduring reference for readers exploring the realms of numerical computation and statistical reasoning.