Probability and statistics

The increase in the requirements on the reliability of units makes it necessary to analyze the relationship between mathematicalmeth- ods of calculating reliability and the physical nature of fail- ures.

Digital sky surveys, high-precision astrometry from satellite data, deep-space data from orbiting telescopes, and the like have all increased the quantity and quality of astronomical data by orders of magnitude per year for several years.

This volume provides a detailed description of a wide range of numerical, statistical or modeling techniques and novel instrumentation separated into individual chapters written by paleontologists with expertise in the given methodology.

The Nelson Mathematics for Cambridge International AS & A Level series is tailored to the needs of A and AS level students of the latest 9709 syllabus.

This book illuminates the fundamental principle and applications of probability-based multi-objective optimization for material selection systematically, in which a brand new concept of preferable probability and its assessment as well as other treatments are introduced by authors for the first time.

Randomized clinical trials are the gold standard for establishing many clinical practice guidelines and are central to evidence based medicine.

The 3-volume set LNAI 13280, LNAI 13281 and LNAI 13282 constitutes the proceedings of the 26th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2022, which was held during May 2022 in Chengdu, China.

This book describes the new generation of discrete choice methods, focusing on the many advances that are made possible by simulation.

United States audience includes 120,000-plus engineering students and 60,000-plus science majors who are required to take a calculus-based statistics courseIncludes examples from MINITAB, EXCEL, STATISTIXS, SAS, SPSS, and MAPLE statistical software programs

Gaussian Markov Random Field (GMRF) models are most widely used in spatial statistics - a very active area of research in which few up-to-date reference works are available.

"e;Overall, this textbook is a perfect guide for interested researchers and students who wish to understand the rationale and methods of causal inference.

This text is a step-by-step, exercise-driven guide for students and practitioners who need to master Excel to solve practical social work problems.

Survival data or more general time-to-event data occur in many areas, including medicine, biology, engineering, economics, and demography, but previously standard methods have requested that all time variables are univariate and independent.

This textbook introduces quantitative methods in operations management, based on operational research.

This richly illustrated book provides an overview of the design and analysis of experiments with a focus on non-clinical experiments in the life sciences, including animal research.

This book provides a broad, mature, and systematic introduction to current financial econometric models and their applications to modeling and prediction of financial time series data.

Modern astronomy has been characterized by an enormous growth in data acquisition - from new technologies in telescopes, detectors, and computation.

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 third edition of this long-selling introductory textbook and ready reference covers all pertinent topics, from basic statistics via modeling and databases right up to the latest regulatory issues.

Studying Human Populations is a textbook for graduate students and research workers in social statistics and related subject areas.

Large sample techniques are fundamental to all fields of statistics.

A unique resource introducing graduate students and researchers in astronomy to advanced statistics through ready-to-use code.

This book connects predictive analytics and simulation analytics, with the end goal of providing Rich Information to stakeholders in complex systems to direct data-driven decisions.

Introduction to Stochastic Finance with Market Examples, Second Edition presents an introduction to pricing and hedging in discrete and continuous-time financial models, emphasizing both analytical and probabilistic methods.

A problem of broad interest - the estimation of the spectral gap for matrices or differential operators (Markov chains or diffusions) - is covered in this book.

This book provides readers with a brief account of the history of Language Identification (LI) research and a survey of the features and methods most used in LI literature.

Data Science in Practice is the ideal introduction to data science.

Perform data analysis with R quickly and efficiently with more than 275 practical recipes in this expanded second edition.

Bayesian statistics has exploded into biology and its sub-disciplines, such as ecology, over the past decade.

This monograph compiles the contemporary knowledge about D-norms and provides an introductory tour through the essentials of multivariate extreme value theory.

The statistical analysis of cost-effectiveness data is becoming increasingly important within health and medical research.

Industrial engineering has expanded from its origins in manufacturing to transportation, health care, logistics, services, and more.

Progressively more and more attention has been paid to how location affects health outcomes.

This text presents a wide variety of common types of models found in other mathematical modeling texts, as well as some new types.

This two-volume set LNAI 7523 and LNAI 7524 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2012, held in Bristol, UK, in September 2012.

This second edition presents up-to-date material on the theory of weak convergance of convolution products of probability measures in semigroups, the theory of random walks on semigroups, and their applications to products of random matrices.

Partial least squares structural equation modelling (PLS-SEM) is becoming a popular statistical framework in many fields and disciplines of the social sciences.

Praise for the First Edition "e;.

The average-case analysis of numerical problems is the counterpart of the more traditional worst-case approach.

Features a straightforward and concise resource for introductory statistical concepts, methods, and techniques using R Understanding and Applying Basic Statistical Methods Using R uniquely bridges the gap between advances in the statistical literature and methods routinely used by non-statisticians.

This second edition focuses on the application of statistical methods in the field of hydrology and hydroclimatology.

"e;Stochastic Tools in Mathematics and Science"e; covers basic stochastic tools used in physics, chemistry, engineering and the life sciences.

Past, Present, and Future of Statistical Science was commissioned in 2013 by the Committee of Presidents of Statistical Societies (COPSS) to celebrate its 50th anniversary and the International Year of Statistics.

Assuming no prior knowledge or technical skills, Getting Started with Business Analytics: Insightful Decision-Making explores the contents, capabilities, and applications of business analytics.

This book allows readers to gain an in-depth understanding of the role of real-world data in pharmacoepidemiology, and highlights the strengths and limitations of the respective databases with regard to pharmacoepidemiological research.