Cancer screening has been carried out for six decades - however, there are many unsolved problems: how to estimate key parameters involved in screenings, such as sensitivity, the time duration in the preclinical state (i.
The Concise Encyclopedia of Statistics presents the essential information about statistical tests, concepts, and analytical methods in language that is accessible to practitioners and students of the vast community using statistics in medicine, engineering, physical science, life science, social science, and business/economics.
This volume covers the latest results on novel methods in Risk Analysis and assessment, with applications in Biostatistics (which is providing food for thought since the first ICRAs, covering traditional areas of RA, until now), Engineering Reliability, the Environmental Sciences and Economics.
This book introduces the basic concepts of set theory, measure theory, the axiomatic theory of probability, random variables and multidimensional random variables, functions of random variables, convergence theorems, laws of large numbers, and fundamental inequalities.
This volume covers the latest results on novel methods in Risk Analysis and assessment, with applications in Biostatistics (which is providing food for thought since the first ICRAs, covering traditional areas of RA, until now), Engineering Reliability, the Environmental Sciences and Economics.
Cancer screening has been carried out for six decades - however, there are many unsolved problems: how to estimate key parameters involved in screenings, such as sensitivity, the time duration in the preclinical state (i.
Value of Information for Healthcare Decision-Making introduces the concept of Value of Information (VOI) use in health policy decision-making to determine the sensitivity of decisions to assumptions, and to prioritise and design future research.
An Introduction to Applied Statistics offers a comprehensive and accessible foundation in applied statistics, empowering students with the essential concepts and practical skills necessary for data-driven decision-making in today's world.
This book provides a comprehensive and systematic introduction to the principal machine learning methods, covering both supervised and unsupervised learning methods.
This book provides a comprehensive and systematic introduction to the principal machine learning methods, covering both supervised and unsupervised learning methods.
This book primarily aims to provide an in-depth understanding of recent advances in big data computing technologies, methodologies, and applications along with introductory details of big data computing models such as Apache Hadoop, MapReduce, Hive, Pig, Mahout in-memory storage systems, NoSQL databases, and big data streaming services such as Apache Spark, Kafka, and so forth.
This book primarily aims to provide an in-depth understanding of recent advances in big data computing technologies, methodologies, and applications along with introductory details of big data computing models such as Apache Hadoop, MapReduce, Hive, Pig, Mahout in-memory storage systems, NoSQL databases, and big data streaming services such as Apache Spark, Kafka, and so forth.
IBM SPSS Statistics 29 Step by Step: A Simple Guide and Reference, eighteenth edition, takes a straightforward, step-by-step approach that makes SPSS software clear to beginners and experienced researchers alike.
Written by an experienced statistics educator and two data scientists, this book unifies conventional statistical thinking and contemporary machine learning framework into a single overarching umbrella over data science.
This book introduces Probability Theory with R software and explains abstract concepts in a simple and easy-to-understand way by combining theory and computation.
Statistics is central in the biosciences, social sciences and other disciplines, yet many students often struggle to learn how to perform statistical tests, and to understand how and why statistical tests work.
Based on the calculation of transition states and the identification of transition paths, this book aims to provide a comprehensive guide to understanding and simulating rare events.
Stochastic processes occur everywhere in the sciences, economics and engineering, and they need to be understood by (applied) mathematicians, engineers and scientists alike.
The emergence of data science, in recent decades, has magnified the need for efficient methodology for analyzing data and highlighted the importance of statistical inference.
This book investigates statistical observables for anomalous and nonergodic dynamics, focusing on the dynamical behaviors of particles modelled by non-Brownian stochastic processes in the complex real-world environment.
This book hosts the results presented at the 6th Bayesian Young Statisticians Meeting 2022 in Montreal, Canada, held on June 22-23, titled "e;Bayesian Statistics, New Generations New Approaches"e;.
This book hosts the results presented at the 6th Bayesian Young Statisticians Meeting 2022 in Montreal, Canada, held on June 22-23, titled "e;Bayesian Statistics, New Generations New Approaches"e;.
