Probability and statistics

Hugely successful and popular text presenting an extensive and comprehensive guide for all R users The R language is recognized as one of the most powerful and flexible statistical software packages, enabling users to apply many statistical techniques that would be impossible without such software to help implement such large data sets.

As many biological products face losing their patents in the next decade, the pharmaceutical industry needs an abbreviated regulatory pathway for approval of biosimilar drug products, which are cost-effective, follow-on/subsequent versions of the innovator's biologic products.

Without question, statistics is one of the most challenging courses for students in the social and behavioral sciences.

This introductory book offers a unique and unified overview of symplectic geometry, highlighting the differential properties of symplectic manifolds.

Lazar Mayants is a recent Russian emigre noted for his work in theoretical physics.

In the evolving field of soil science, advanced statistical analysis has become essential for understanding complex soil processes.

Introductory Statistical Inference develops the concepts and intricacies of statistical inference.

This volume, Statistical Methods in Psychiatry Research and SPSS, now going into its second edition, has been helping psychiatrists expand their knowledge of statistical methods and fills the gaps in their applications as well as introduces data analysis software.

This book is comprised of presentations delivered at the 5th Workshop on Biostatistics and Bioinformatics held in Atlanta on May 5-7, 2017.

This book covers the issues related to optimization of engineering and management problems using soft computing techniques with an industrial outlook.

This collection of essays is in honor of Shizuhiko Nishisato on his 88th birthday and consists of invited contributions only.

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

As a mathematical model for determining the probable number of outcomes, the new Poisson Distribution tables have long been an easier tool to use for reliability analyses.

This compilation focuses on the theory and conceptualisation of statistics and probability in the early years and the development of young children's (ages 3-10) understanding of data and chance.

Concentration inequalities for functions of independent random variables is an area of probability theory that has witnessed a great revolution in the last few decades, and has applications in a wide variety of areas such as machine learning, statistics, discrete mathematics, and high-dimensional geometry.

This book provides new theoretic and applied material with focus on quantitative methods and data analysis techniques applied in demography, population studies, health issues and statistics.

This book explores the most important processing steps of proteomics data analysis and presents practical guidelines, as well as software tools, that are both user-friendly and state-of-the-art in chemo- and biostatistics.

This book explores mathematics in a wide variety of applications, ranging from problems in electronics, energy and the environment, to mechanics and mechatronics.

Scientists often collect samples of curves and other functional observations, and develop models where parameters are also functions.

The brief will describe how to develop a risk analysis applied to a project , through a sequence of steps: risk management planning, risk identification, risk classification, risk assessment, risk quantification, risk response planning, risk monitoring and control, process close out and lessons learning.

While the primary purpose of the book is a celebration of John's contributions to the field of measurement, a second and related purpose is to provide a useful resource.

This monograph is a progressive introduction to non-commutativity in probability theory.

Probabilistic Foundations of Statistical Network Analysis presents a fresh and insightful perspective on the fundamental tenets and major challenges of modern network analysis.

This accessible textbook demonstrates how to recognize, simplify, model and solve optimization problems – and apply these principles to new projects.

This monograph aims to promote original mathematical methods to determine the invariant measure of two-dimensional random walks in domains with boundaries.

Reinforcement learning (RL) is a framework for decision making in unknown environments based on a large amount of data.

Modern ecological and environmental sciences are dominated by observational data.

Baseball is not the only sport to use "e;moneyball.

This monograph and translation from the Russian describes in detail and comments on the fundamentals of metrology.

Are you buying a car or smartphone or dishwasher?

Highlighting the latest advances in stochastic analysis and its applications, this volume collects carefully selected and peer-reviewed papers from the 5th International Conference on Stochastic Methods (ICSM-5), held in Moscow, Russia, November 23-27, 2020.

This book provides a systematic and general theory of probability within the framework of constructive mathematics.

Uncertainty Quantification (UQ) is an emerging and extremely active research discipline which aims to quantitatively treat any uncertainty in applied models.

In this textbook, basic mathematical models used in Big Data Analytics are presented and application-oriented references to relevant practical issues are made.

Statistical Methods: An Introduction to Basic Statistical Concepts and Analysis, Second Edition is a textbook designed for students with no prior training in statistics.

Starting from the preliminaries and ending with live examples, Modern Survey Sampling details what a sample can communicate about an unknowable aggregate in a real situation.

Set-Indexed Martingales offers a unique, comprehensive development of a general theory of Martingales indexed by a family of sets.

This monograph provides a concise point of research topics and reference for modeling correlated response data with time-dependent covariates, and longitudinal data for the analysis of population-averaged models, highlighting methods by a variety of pioneering scholars.

This Festschrift celebrates Teddy Seidenfeld and his seminal contributions to philosophy, statistics, probability, game theory and related areas.

An almost complete collection of the papers given at the International Workshop on Imaging in High Energy Astronomy (Anacapri, Italy, 1994).

Interest in brain connectivity inference has become ubiquitous and is now increasingly adopted in experimental investigations of clinical, behavioral, and experimental neurosciences.

There have been major developments in the field of statistics over the last quarter century, spurred by the rapid advances in computing and data-measurement technologies.

Stochastic Differential Equations for Science and Engineering is aimed at students at the M.

Probability is tough - even those fairly well versed in statistical analysis balk at the prospect of tackling it.

This handbook is a comprehensive reference guide for researchers, funding agencies and organizations engaged in survey research.

This book includes the proceedings of the Workshop held in Madrid, April 1999 to celebrate 2 years of successful operation of the first Spanish small scientific satellite in orbit.