Probability and statistics

This book is based on over a dozen years teaching a Bayesian Statistics course.

A hands-on guide to using R to carry out key statistical practices in educational and behavioral sciences research Computing has become an essential part of the day-to-day practice of statistical work, broadening the types of questions that can now be addressed by research scientists applying newly derived data analytic techniques.

This book offers accessible probabilistic modelling of relevant financial problems.

This book offers a broad selection of statistical applications to everyday situations, illustrating how exciting and diverse statistical analysis can be.

The modeling of item response data is governed by item response theory, also referred to as modern test theory.

Filling a gap in current Bayesian theory, Statistical Inference: An Integrated Bayesian/Likelihood Approach presents a unified Bayesian treatment of parameter inference and model comparisons that can be used with simple diffuse prior specifications.

Recent advances in digitization are transforming healthcare, education, tourism, information technology, and some other sectors.

Mathematical Tools for Applied Multivariate Analysis provides information pertinent to the aspects of transformational geometry, matrix algebra, and the calculus that are most relevant for the study of multivariate analysis.

Intelligent Information Technology (iiT) encompasses the theories and ap- plications of artificial intelligence, statistical pattern recognition, learning theory, data warehousing, data mining and knowledge discovery, Grid com- puting, and autonomous agents and multi-agent systems in the context of today's as well as future IT, such as Electronic Commerce (EC), Business Intelligence (BI), Social Intelligence (SI), Web Intelligence (WI), Knowledge Grid (KG), and Knowledge Community (KC), among others.

The peer-reviewed contributions gathered in this book address methods, software and applications of statistics and data science in the social sciences.

Mathematica is a computer program (software) for doing symbolic, numeric and graphical analysis of mathematical problems.

Modern statistics deals with large and complex data sets, and consequently with models containing a large number of parameters.

This book examines the latest developments in Artificial Intelligence (AI)-based metaheuristics algorithms with applications in information security for digital media.

In the last few years, Qualitative Comparative Analysis (QCA) has become one of the most important research approaches in social science.

Sentiment analysis research has been started long back and recently it is one of the demanding research topics.

Senior probabilists from around the world with widely differing specialities gave their visions of the state of their specialty, why they think it is important, and how they think it will develop in the new millenium.

In der IT-Organisation geht es um die zuverlässige, zeit-, kosten- und qualitätsoptimale Bereitstellung geschäftsprozessunterstützender IT-Dienstleistungen.

Interval-Censored Time-to-Event Data: Methods and Applications collects the most recent techniques, models, and computational tools for interval-censored time-to-event data.

This beginning graduate textbook teaches data science and machine learning methods for modeling, prediction, and control of complex systems.

This book provides detailed empirical analysis of countries in Asia to examine various dynamic models that incorporate the impact of technology and innovations on the industry evolution and overall economic growth.

This textbook addresses postgraduate students in applied mathematics, probability, and statistics, as well as computer scientists, biologists, physicists and economists, who are seeking a rigorous introduction to applied stochastic processes.

This book provides an inter-disciplinary introduction to the theory of random fields and its applications.

This book introduces computational advertising, and Internet monetization.

This textbook provides an exciting new addition to the area of network science featuring a stronger and more methodical link of models to their mathematical origin and explains how these relate to each other with special focus on epidemic spread on networks.

This book details cutting-edge research into human-like driving technology, utilising game theory to better suit a human and machine hybrid driving environment.

Examines Critical Decisions for Transitioning Lab Science to a Clinical SettingThe development of therapeutic pharmaceutical compounds is becoming more expensive, and the success rates for getting such treatments approved for marketing and to the patients is decreasing.

Markov decision processes (MDPs), also called stochastic dynamic programming, were first studied in the 1960s.

Biostatistics, Second Edition, is a user-friendly guide on biostatistics, which focuses on the proper use and interpretation of statistical methods.

Can you really keep your eye on the ball?

Nonlinear dynamics is now recognized as playing a crucialrole in a wide variety of disciplines.

This book shows the capabilities of Microsoft Excel in teaching physical science statistics effectively.

Given a set of objects and a pairwise similarity measure between them, the goal of correlation clustering is to partition the objects in a set of clusters to maximize the similarity of the objects within the same cluster and minimize the similarity of the objects in different clusters.

Cyclic and Computer Generated Designs is a much-expanded and updated version of the well-received monograph, Cyclic Designs .

The present volume is an extensive monograph on the analytic and geometric aspects of Markov diffusion operators.

There have been many advances in the theory and applications of discrete distributions in recent years.

The field of high-throughput genetic experimentation is evolving rapidly, with the advent of new technologies and new venues for data mining.

Piecewise-deterministic Markov processes form a class of stochastic models with a sizeable scope of applications: biology, insurance, neuroscience, networks, finance.

Use this practical guide to the Splunk operational data intelligence platform to search, visualize, and analyze petabyte-scale, unstructured machine data.

The cooperation and contamination among mathematicians, statisticians and econometricians working in actuarial sciences and finance are improving the research on these topics and producing numerous meaningful scientific results.

Probability and Statistical Inference: From Basic Principles to Advanced Models covers aspects of probability, distribution theory, and inference that are fundamental to a proper understanding of data analysis and statistical modelling.

The main subject is the probabilistic extreme value theory.

A greatly expanded and heavily revised second edition, this popular guide provides instructions and clear examples for running analyses of variance (ANOVA) and several other related statistical tests of significance with SPSS.

The brand new edition of this classic text--with more exercises andeasier to use than ever Like the first edition, this new version ofLamperti's classic text succeeds in making this fascinating area ofmathematics accessible to readers who have limited knowledge ofmeasure theory and only some familiarity with elementaryprobability.

This book introduces econometric analysis of cross section, time series and panel data with the application of statistical software.

Survival analysis uses statistics to calculate time to failure.