Probability and statistics

This book presents a comprehensive overview of Structural Equation Modeling and how it can be applied to address research issues in different disciplines.

This book covers all the topics found in introductory descriptive statistics courses, including simple linear regression and time series analysis, the fundamentals of inferential statistics (probability theory, random sampling and estimation theory), and inferential statistics itself (confidence intervals, testing).

The primary goal of this text is a practical one.

Analysis of Categorical Data with R, Second Edition presents a modern account of categorical data analysis using the R software environment.

The leading traits of executives often include creativity and innovation.

Today, machine learning is being applied to a growing variety of problems in a bewildering variety of domains.

Today, machine learning is being applied to a growing variety of problems in a bewildering variety of domains.

Multiscale geographically weighted regression (MGWR) is an important method that is used across many disciplines for exploring spatial heterogeneity and modeling local spatial processes.

Multiscale geographically weighted regression (MGWR) is an important method that is used across many disciplines for exploring spatial heterogeneity and modeling local spatial processes.

This book covers unsupervised learning, supervised learning, clustering approaches, feature engineering, explainable AI and multioutput regression models for subsurface engineering problems.

This book presents state-of-the-art optimization algorithms followed by Internet of Things (IoT) fundamentals.

This book presents state-of-the-art optimization algorithms followed by Internet of Things (IoT) fundamentals.

This book provides an overview of statistical concepts and basic methodology for the study of genetics of human traits and diseases.

This book provides an overview of statistical concepts and basic methodology for the study of genetics of human traits and diseases.

This book offers a comprehensive examination of the Cramer-Lundberg model, which is the most extensively researched model in ruin theory.

This book explores the multiple facets of habit from diverse and complementary theoretical frameworks.

Bayesian data analysis and modelling linked with machine learning offers a new tool for handling geotechnical data.

This book not only presents essential material to understand fuzzy metric fixed point theory, but also enables the readers to appreciate the recent advancements made in this direction.

This book provides an overview of recent work on developing a theory of statistical inference based on measuring statistical evidence.

Data Science for Sensory and Consumer Scientists is a comprehensive textbook that provides a practical guide to using data science in the field of sensory and consumer science through real-world applications.

This book explains the best practices of the UNCTAD & WTO for trade analysis to the R users community.

Linear Models and the Relevant Distributions and Matrix Algebra: A Unified Approach, Volume 2 covers several important topics that were not included in the first volume.

The book offers insight into the healthcare system by exploring emerging technologies and AI-based applications and implementation strategies.

This book is a guide to non-academic careers for quantitative social scientists.

This book provides an introduction to computer-based methods for the analysis of genomic data.

This book presents the foundations of using analytics from the laboratory, social media platforms, and the web.

This book summarises for the first time all relevant methodologies for type-based flood statistics, introduces the basis of flood typology and makes them accessible to the user.

This book is a guide to non-academic careers for quantitative social scientists.

Linear Models and the Relevant Distributions and Matrix Algebra: A Unified Approach, Volume 2 covers several important topics that were not included in the first volume.

Models for Non-Modelers focuses not on how to design models but on how to understand and critically appraise them.

Data Science for Sensory and Consumer Scientists is a comprehensive textbook that provides a practical guide to using data science in the field of sensory and consumer science through real-world applications.

Forecasting and Analytics with the Augmented Dynamic Adaptive Model (ADAM) focuses on a time series model in Single Source of Error state space form, called "e;ADAM"e; (Augmented Dynamic Adaptive Model).

This book explains the best practices of the UNCTAD & WTO for trade analysis to the R users community.

This book addresses the description and analysis of occurrence data frequently encountered in epidemiological studies.

This book summarises for the first time all relevant methodologies for type-based flood statistics, introduces the basis of flood typology and makes them accessible to the user.

For thousands of years, music has acted as a powerful medium for evoking emotions, facilitating communication, and nurturing overall well-being.

For thousands of years, music has acted as a powerful medium for evoking emotions, facilitating communication, and nurturing overall well-being.