The Fundamentals of Statistics for Data Science From Descriptive Statistics to Predictive Analytics

The Fundamentals of Statistics for Data Science: From Descriptive Statistics to Predictive Analytics is a comprehensive textbook that introduces the fundamental concepts of statistics required for modern data science, artificial intelligence, machine learning, and business analytics. It provides a systematic approach to understanding statistical methods, enabling readers to analyze data, draw meaningful conclusions, and make informed, data-driven decisions. The book covers essential topics including probability, probability distributions, sampling techniques, estimation, hypothesis testing, quality control, regression, correlation, ANOVA, Chi-Square tests, and non-parametric methods. Each chapter is presented in a clear and easy-to-understand manner, supported by practical examples, solved problems, and comparison tables that help bridge the gap between theory and real-world applications. Designed for undergraduate and postgraduate students, educators, researchers, and industry professionals, this book serves as both a learning resource and a practical reference. Whether you are beginning your journey in statistics or strengthening your analytical skills for data science and predictive analytics, this book provides the knowledge and confidence needed to transform data into meaningful insights and informed decisions.