Advanced Statistical And Computational Techniques in Interdisciplinary Research Edition 2025,PB

The book Advanced Statistical and Computational Techniques in Interdisciplinary Research (Edition 2025, Paperback) is a comprehensive academic resource designed for modern researchers working across multiple disciplines. It focuses on advanced methodologies that combine statistical analysis with computational techniques to solve complex real-world problems. The book covers essential topics such as multivariate analysis, regression modeling, hypothesis testing, time-series analysis, and Bayesian statistics. It further expands into computational methods including machine learning algorithms, data mining, simulation techniques, and artificial intelligence-based modeling. A key strength of this edition is its interdisciplinary approach, demonstrating how statistical and computational tools can be applied across fields such as healthcare, environmental science, economics, engineering, and social sciences. It emphasizes data interpretation, predictive modeling, and evidence-based decision-making. The book also includes practical case studies, real datasets, and step-by-step explanations to help readers apply theoretical concepts effectively. It addresses challenges in handling big data, ensuring accuracy, and selecting appropriate analytical methods for different research scenarios. Ideal for PhD scholars, postgraduate students, data scientists, and academic researchers, this book serves as a bridge between traditional statistical theory and modern computational research practices. It ultimately supports innovation, accuracy, and efficiency in interdisciplinary research environments.