Probability and statistics

Access and clean up data easily using JMP(R)!

The apparent contradiction between statistical significance and biological relevance has diminished the value of statistical methods as a whole in toxicology.

This book provides engineers and scientists with a single source introduction to the concepts, models, and case studies for making credible reliability assessments.

The contributions in this book were presented at the Fourth International Geostatistics Congress held in Troia, Portugal, in September 1992.

For every problem, mathematical or otherwise, there is more than one approach and much depends on the ingenuity of the person concerned.

This book combines theoretical underpinnings of statistics with practical analysis of Earth sciences data using MATLAB.

A graduate level textbook on probabilistic risk analysis, aimed at statisticians, operations researchers and engineers.

Aufbauend auf der Schulmathematik, d.

This book of peer-reviewed contributions presents the latest findings in classification, statistical learning, data analysis and related areas, including supervised and unsupervised classification, clustering, statistical analysis of mixed-type data, big data analysis, statistical modeling, graphical models and social networks.

Winner of the 2017 De Groot Prize awarded by the International Society for Bayesian Analysis (ISBA)A relatively new area of research, adversarial risk analysis (ARA) informs decision making when there are intelligent opponents and uncertain outcomes.

This book is dedicated to modern approaches to mathematical modeling of reflexive processes in control.

First derived within the context of life-testing, inverse Gaussian distribution has become one of the most important and widely employed distributions, and is often used to model the lifetimes of components.

Hereditary systems (or systems with either delay or after-effects) are widely used to model processes in physics, mechanics, control, economics and biology.

This empirical research methods course enables informed implementation of statistical procedures, giving rise to trustworthy evidence.

The intention of this collection agrees with the purposes of the homonymous mini-symposium (MS) at ICIAM-2019, which were to overview the essentials of geometric calculus (GC) formalism, to report on state-of-the-art applications showcasing its advantages and to explore the bearing of GC in novel approaches to deep learning.

This textbook invites readers to explore mathematical thinking by finding the beauty in the subject.

Reliability and maintenance modeling with optimization is the most fundamental and interdisciplinary research area that can be applied to every technical and management field.

This book describes many types of Conference matrices and shows the case studies of application.

Planning of actions based on decision theory is a hot topic for many disciplines.

Operations research uses quantitative models to analyze and predict the behavior of systems and to provide information for decision makers.

With its emphasis on practical and conceptual aspects, rather than mathematics or formulas, this accessible book has established itself as the go-to resource on confirmatory factor analysis (CFA).

The seventh edition of Research Methods and Statistics in Psychology provides students with the most readable and comprehensive survey of research methods, statistical concepts and procedures in psychology today.

Bayesian Nonparametrics for Causal Inference and Missing Data provides an overview of flexible Bayesian nonparametric (BNP) methods for modeling joint or conditional distributions and functional relationships, and their interplay with causal inference and missing data.

IBM SPSS Statistics 27 Step by Step: A Simple Guide and Reference, seventeenth edition, takes a straightforward, step-by-step approach that makes SPSS software clear to beginners and experienced researchers alike.

The goal of this book is multidimensional: a) to help reviving Statistics education in many parts in the world where it is in crisis.

This monograph is a slightly revised version of my PhD thesis [86], com- pleted in the Department of Computer Science at the University of Edin- burgh in June 1988, with an additional chapter summarising more recent developments.

Focusing on methodologies, applications and challenges of textual data analysis and related fields, this book gathers selected and peer-reviewed contributions presented at the 14th International Conference on Statistical Analysis of Textual Data (JADT 2018), held in Rome, Italy, on June 12-15, 2018.

Bayesian analysis of complex models based on stochastic processes has in recent years become a growing area.

This book introduces various mathematical models used in ecological risk assessment, primarily discussing models used in hazard assessment.

New up-to-date edition of this influential classic - the bible on Markov chains in general state spaces is back.

This book illustrates the EU-wide Solvency II framework for the insurance industry, which was implemented on January 1, 2016, after a long project phase.

Keine ausführliche Beschreibung für "Handbuch zur Anwendung" verfügbar.

There is an increasing need for educational resources for statisticians and investigators.

Revealing the limitations of human decision-making, this book explores how Artificial Intelligence (AI) can be used to optimize decisions for improved business outcomes and efficiency, as well as looking ahead to the significant contributions Decision Intelligence (DI) can make to society and the ethical challenges it may raise.

This unique book presents decision analysis in the context of mathematical modeling and game theory.

For years, organizations have struggled to make sense out of their data.

The history of many sciences is characterized by an almost continuous emer- gence of new theories.

This book describes official statistics as a tool to hold up a mirror to society - but also as an instrument for those who can manipulate this mirror.

This book introduces environmental, social and governance (ESG) investment and clarifies its characteristics as financial securities.

High-Performance Computing for Big Data: Methodologies and Applications explores emerging high-performance architectures for data-intensive applications, novel efficient analytical strategies to boost data processing, and cutting-edge applications in diverse fields, such as machine learning, life science, neural networks, and neuromorphic engineering.

This thoroughly updated second edition combines the latest software applications with the benefits of modern resampling techniques Resampling helps students understand the meaning of sampling distributions, sampling variability, P-values, hypothesis tests, and confidence intervals.

Power markets are undergoing a major transformation from gas and oil-fueled generation toward renewable electricity production from wind and solar sources.

This book reports on the latest advances andapplications of chaotic systems.

Topological Methods for Differential Equations and Inclusions covers the important topics involving topological methods in the theory of systems of differential equations.