Azizur Rahman – författare

Small Area Estimation and Microsimulation Modeling is the first practical handbook that comprehensively presents modern statistical SAE methods in the framework of ultramodern spatial microsimulation modeling while providing the novel approach of creating synthetic spatial microdata. Along with describing the necessary theories and their advantages and limitations, the authors illustrate the practical application of the techniques to a large number of substantive problems, including how to build up models, organize and link data, create synthetic microdata, conduct analyses, yield informative tables and graphs, and evaluate how the findings effectively support the decision making processes in government and non-government organizations.FeaturesCovers both theoretical and applied aspects for real-world comparative research and regional statistics productionThoroughly explains how microsimulation modeling technology can be constructed using available datasets for reliable small area statisticsProvides SAS codes that allow readers to utilize these latest technologies in their own work.This book is designed for advanced graduate students, academics, professionals and applied practitioners who are generally interested in small area estimation and/or microsimulation modeling and dealing with vital issues in social and behavioural sciences, applied economics and policy analysis, government and/or social statistics, health sciences, business, psychology, environmental and agriculture modeling, computational statistics and data simulation, spatial statistics, transport and urban planning, and geospatial modeling.

Innovations and Human Factors Challenges in Healthcare Product Design covers best practices and advanced design methods to capture, document, and validate various challenges at the early stage of the design process, also delving into how to mitigate design strategies to address those challenges without compromising the cost, effort, safety, and quality of the device. The book provides a comprehensive collection of technical notes, research designs, design methods and processes, case studies, comprehensive literature on the industrial impact of design methods and processes, and applications of digital technologies for design, analysis, manufacturing, testing, and deployment. Readers will find multidisciplinary coverage of the application of technology and science for product design in healthcare sectors.Offers a comprehensive exploration of innovations and challenges in healthcare product designFeatures contributions from experts and thought leaders in healthcare design, offering valuable insights and perspectives from professionals who are at the forefront of innovation in the industryExplores the integration of cutting-edge technologies, such as artificial intelligence, telemedicine, wearables, and data analytics, into healthcare product design

This book covers computational statistics-based approaches for Artificial Intelligence. The aim of this book is to provide comprehensive coverage of the fundamentals through the applications of the different kinds of mathematical modelling and statistical techniques and describing their applications in different Artificial Intelligence systems. The primary users of this book will include researchers, academicians, postgraduate students, and specialists in the areas of data science, mathematical modelling, and Artificial Intelligence. It will also serve as a valuable resource for many others in the fields of electrical, computer, and optical engineering.The key features of this book are:Presents development of several real-world problem applications and experimental research in the field of computational statistics and mathematical modelling for Artificial IntelligenceExamines the evolution of fundamental research into industrialized research and the transformation of applied investigation into real-time applicationsExamines the applications involving analytical and statistical solutions, and provides foundational and advanced concepts for beginners and industry professionalsProvides a dynamic perspective to the concept of computational statistics for analysis of data and applications in intelligent systems with an objective of ensuring sustainability issues for ease of different stakeholders in various fieldsIntegrates recent methodologies and challenges by employing mathematical modeling and statistical techniques for Artificial Intelligence

This book covers computational statistics-based approaches for Artificial Intelligence. The aim of this book is to provide comprehensive coverage of the fundamentals through the applications of the different kinds of mathematical modelling and statistical techniques and describing their applications in different Artificial Intelligence systems. The primary users of this book will include researchers, academicians, postgraduate students, and specialists in the areas of data science, mathematical modelling, and Artificial Intelligence. It will also serve as a valuable resource for many others in the fields of electrical, computer, and optical engineering.The key features of this book are:Presents development of several real-world problem applications and experimental research in the field of computational statistics and mathematical modelling for Artificial IntelligenceExamines the evolution of fundamental research into industrialized research and the transformation of applied investigation into real-time applicationsExamines the applications involving analytical and statistical solutions, and provides foundational and advanced concepts for beginners and industry professionalsProvides a dynamic perspective to the concept of computational statistics for analysis of data and applications in intelligent systems with an objective of ensuring sustainability issues for ease of different stakeholders in various fieldsIntegrates recent methodologies and challenges by employing mathematical modeling and statistical techniques for Artificial Intelligence

In an era marked by exponential growth in data generation and an unprecedented convergence of technology and healthcare, the intersection of biostatistics and data science has become a pivotal domain. This book is the ideal companion in navigating the convergence of statistical methodologies and data science techniques with diverse applications implemented in the open-source environment of R. It is designed to be a comprehensive guide, marrying the principles of biostatistics with the practical implementation of statistics and data science in R, thereby empowering learners, researchers, and practitioners with the tools necessary to extract meaningful knowledge from biological, health, and medical datasets.This book is intended for students, researchers, and professionals eager to harness the combined power of biostatistics, data science, and the R programming language while gathering vital statistical knowledge needed for cutting-edge scientists in all fields. It is useful for those seeking to understand the basics of data science and statistical analysis, or looking to enhance their skills in handling any simple or complex data including biological, health, medical, and industry data.Key Features:Presents contemporary concepts of data science and biostatistics with real-life data analysis examplesPromotes the evolution of fundamental and advanced methods applying to real-life problem-solving casesExplores computational statistical data science techniques from initial conception to recent developments of biostatisticsProvides all R codes and real-world datasets to practice and competently apply into reader’s own domainsWritten in an exclusive state-of-the-art deductive approach without any theoretical hitches to support all contemporary readers

Small Area Estimation and Microsimulation Modeling is the first practical handbook that comprehensively presents modern statistical SAE methods in the framework of ultramodern spatial microsimulation modeling while providing the novel approach of creating synthetic spatial microdata. Along with describing the necessary theories and their advantages and limitations, the authors illustrate the practical application of the techniques to a large number of substantive problems, including how to build up models, organize and link data, create synthetic microdata, conduct analyses, yield informative tables and graphs, and evaluate how the findings effectively support the decision making processes in government and non-government organizations.Features Covers both theoretical and applied aspects for real-world comparative research and regional statistics production Thoroughly explains how microsimulation modeling technology can be constructed using available datasets for reliable small area statistics Provides SAS codes that allow readers to utilize these latest technologies in their own work.This book is designed for advanced graduate students, academics, professionals and applied practitioners who are generally interested in small area estimation and/or microsimulation modeling and dealing with vital issues in social and behavioural sciences, applied economics and policy analysis, government and/or social statistics, health sciences, business, psychology, environmental and agriculture modeling, computational statistics and data simulation, spatial statistics, transport and urban planning, and geospatial modeling. Dr Azizur Rahman is a Senior Lecturer in Statistics and convenor of the Graduate Program in Applied Statistics at the Charles Sturt University, and an Adjunct Associate Professor of Public Health and Biostatistics at the University of Canberra. His research encompasses small area estimation, applied economics, microsimulation modeling, Bayesian inference and public health. He has more than 60 scholarly publications including two books. Dr. Rahman’s research is funded by the Australian Federal and State Governments, and he serves on a range of editorial boards including the International Journal of Microsimulation (IJM). Professor Ann Harding, AO is an Emeritus Professor of Applied Economics and Social Policy at the National Centre for Social and Economic Modelling (NATSEM) of the University of Canberra. She was the founder and inaugural Director of this world class Research Centre for more than sixteen years, and also a co-founder of the International Microsimulation Association (IMA) and served as the inaugural elected president of IMA from 2004 to 2011. She is a fellow of the Academy of the Social Sciences in Australia. She has more than 300 publications including several books in microsimulation modeling.

This book brings together the best contributions of the Applied Statistics and Policy Analysis Conference 2019. Written by leading international experts in the field of statistics, data science and policy evaluation. This book explores the theme of effective policy methods through the use of big data, accurate estimates and modern computing tools and statistical modelling.

This book brings together the best contributions of the Applied Statistics and Policy Analysis Conference 2019. This book explores the theme of effective policy methods through the use of big data, accurate estimates and modern computing tools and statistical modelling.

This book presents innovative work by leading academics, researchers, and experts from industry which is useful for young researchers and students.