Statistical Inference

Statistical Inference: From Probability to Evidence: Estimation, Hypothesis Testing, ANOVA, Regression, and Applications This book provides a comprehensive and accessible introduction to the principles and practices of statistical inference. The book presents essential concepts, formulas, assumptions, and applications in a systematic manner, helping readers understand how statistical evidence can be used to draw conclusions from sample data. Covering probability and distributions, estimation, hypothesis testing, nonparametric methods, ANOVA, regression analysis, categorical data analysis, and modern resampling approaches, the book connects statistical theory with practical research applications. Clear explanations and structured presentations are designed to support readers in understanding not only how statistical procedures are performed, but also why and when particular methods should be used. Written for students, lecturers, researchers, academics, scientists, and policymakers, this book can serve as a practical reference for quantitative research and evidence-based decision-making. It is particularly relevant to readers in education, social sciences, mathematics, health sciences, business, engineering, and other fields where statistical inference plays an important role. By integrating theory, formulas, methodological principles, and applications, this book aims to strengthen statistical reasoning and promote the appropriate interpretation of quantitative evidence. It provides a useful foundation for readers seeking to develop confidence in applying inferential statistical techniques in academic research and professional practice.