Numerical Methods for Statistical Computation: Theory, Algorithms, and Applications bridges numerical analysis with modern statistics, offering a unified treatment of root-finding, linear systems, interpolation, integration, differential equations, and optimization all within a statistical framework. Through detailed theory, worked examples, and real applications, the book equips readers to solve complex statistical problems numerically. Designed for advanced undergraduates, graduate students, and researchers in statistics and data science, it emphasizes both algorithmic understanding and...

Unlocking Data with SPSS: From Curiosity to Competence is a complete and practical guide designed to lead students, researchers, and professionals from the basics of SPSS to advanced statistical techniques. Beginning with an intuitive introduction to SPSS software, readers learn how to define variables, manage data, and conduct essential descriptive statistics and visualizations. As the book progresses, it builds a strong foundation in inferential statistics, including hypothesis testing, t-tests, ANOVA, regression analysis, and non-parametric methods. Advanced topics like factor analysis,...

"Sampling Techniques: From Fundamentals to Advanced Applications" is a comprehensive guide that covers both classical and modern approaches to sampling. Aimed at master's level students and professionals, the book blends theory, real-world applications, and computational tools.It begins with core sampling concepts and classical methods like SRS, stratified, and cluster sampling, then advances to specialized topics including adaptive sampling, Bayesian methods, and model-assisted techniques. Each chapter includes theorems, proofs, examples, illustrations, exercises with solutions, and coding...

Statistics, as a field of study, is no longer confined to academic circles or specialized research domains. It has evolved into a foundational discipline that intersects with every facet of modern life from policy formulation and business decision making to public health, technology, and everyday reasoning. The demand for clarity, conceptual depth, and real-world relevance in the teaching of statistics has never been greater.This book is particularly tailored for undergraduate students in statistics and allied disciplines, including economics, commerce, data science, and social sciences. It...