Probability and statistics

Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan, Second Edition provides an accessible approach for conducting Bayesian data analysis, as material is explained clearly with concrete examples.

Although many books currently available describe statistical models and methods for analyzing longitudinal data, they do not highlight connections between various research threads in the statistical literature.

This book is meant to be a practical introduction into the use of probability and statistics in experimental physics for advanced undergraduate students and for graduate students.

Besides a number of papers on classical areas of research in probability such as martingale theory, Malliavin calculus and 2-parameter processes, this new volume of the Séminaire de Probabilités develops the following themes: - chaos representation for some new kinds of martingales, - quantum probability, - branching aspects on Brownian excursions, - Brownian motion on a set of rays.

Presents basic and advanced methods with a focus on demonstrated added value for a broad class of public health surveillance problems.

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

A well-balanced and accessible introduction to the elementary quantitative methods and Microsoft Office Excel applications used to guide business decision making Featuring quantitative techniques essential for modeling modern business situations, Introduction to Quantitative Methods in Business: With Applications Using Microsoft Office Excel provides guidance to assessing real-world data sets using Excel.

Statistical Approaches in Oncology Clinical Development : Current Paradigm and Methodological Advancement presents an overview of statistical considerations in oncology clinical trials, both early and late phase of development.

Masatoshi Fukushima is one of the most influential probabilists of our times.

Technological improvements continue to push back the frontier of processor speed in modern computers.

Analysis of Genetic Association Studies is both a graduate level textbook in statistical genetics and genetic epidemiology, and a reference book for the analysis of genetic association studies.

Interest in multilevel statistical models for social science and public health studies has been aroused dramatically since the mid-1980s.

This book is specially designed to refresh and elevate the level of understanding of the foundational background in probability and distributional theory required to be successful in a graduate-level statistics program.

A comprehensive and up-to-date introduction to the mathematics that all economics students need to knowProbability theory is the quantitative language used to handle uncertainty and is the foundation of modern statistics.

This book offers a thorough understanding of Hierarchical Archimedean Copulas (HACs) and their practical applications.

Generate and Analyze Multi-Level Data Spatial microsimulation involves the generation, analysis, and modeling of individual-level data allocated to geographical zones.

A mathematically rigorous, practical introduction presenting standard topics plus research.

Regression analysis of cause effect relationships is increasingly the core of medical and health research.

Praise for Common Errors in Statistics (and How to Avoid Them) "e;A very engaging and valuable book for all who use statistics in any setting.

RicochetConfessions Of A Gun Lobbyist"e;Ricochet tells the truth.

Time Series: A First Course with Bootstrap Starter provides an introductory course on time series analysis that satisfies the triptych of (i) mathematical completeness, (ii) computational illustration and implementation, and (iii) conciseness and accessibility to upper-level undergraduate and M.

How much statistics does a clinician, surgeon or nurse need to know?

Guides You on the Development and Implementation of B-R EvaluationsBenefit-Risk Assessment Methods in Medical Product Development: Bridging Qualitative and Quantitative Assessments provides general guidance and case studies to aid practitioners in selecting specific benefit-risk (B-R) frameworks and quantitative methods.

Amongmanyexcitingdevelopmentsinstatisticsoverthelasttwodecades, nonlineartimeseriesanddata-analyticnonparametricmethodshavegreatly advanced along seemingly unrelated paths.

Want to use the power of R sooner rather than later?

This book is about doing microeconometrics, defined by Cameron and Trivedi as "e;the analysis of individual-level data on the economic behavior of individuals or firms using regression methods applied to cross-section and panel data"e; with R.

This textbook presents an overview of the field of demography from a contemporary perspective.

This book includes a novel motif discovery for time series, KITE (ill-Known motIf discovery in Time sEries data), to identify ill-known motifs transformed by affine mappings such as translation, uniform scaling, reflection, stretch, and squeeze mappings.

A readable, digestible introduction to essential theory and wealth of applications, with a vast set of examples and numerous exercises.

Since the publication of the second edition of Applied Reliability in 1995, the ready availability of inexpensive, powerful statistical software has changed the way statisticians and engineers look at and analyze all kinds of data.

This brief monograph is an in-depth study of the infinite divisibility and self-decomposability properties of central and noncentral Student's distributions, represented as variance and mean-variance mixtures of multivariate Gaussian distributions with the reciprocal gamma mixing distribution.

Cost-effectiveness analysis is becoming an increasingly important tool for decision making in the health systems.

A comprehensive guide to statistical hypothesis testing with examples in SAS and R When analyzing datasets the following questions often arise: Is there a short hand procedure for a statistical test available in SAS or R?

Advances in Growth Curve Models: Topics from the Indian Statistical Institute is developed from the Indian Statistical Institute's A National Conference on Growth Curve Models.

Noted for its integration of real-world data and case studies, this text offers sound coverage of the theoretical aspects of mathematical statistics.

Over the past decade, Big Data have become ubiquitous in all economic sectors, scientific disciplines, and human activities.

These notes, based on lectures delivered in Saint Flour, provide an easy introduction to the authors' 2007 Springer monograph "e;Random Fields and Geometry.

If something can fail, it can often fail in one of several ways and sometimes in more than one way at a time.

International experts from around the globe present a rich variety of intriguing developments in time series analysis in hydrology and environmental engineering.

This is the second edition of Linear Models for Multivariate, Time Series and Spatial Data.

The book reports on the development of householdfinances in rural China.

This practical guide is designed for students and researchers with an existing knowledge of R who wish to learn how to apply it in an epidemiological context and exploit its versatility.

This book generalizes and extends the available theory in robust and decentralized hypothesis testing.

This book discusses the payout phase of the old-age pension saving scheme, the so-called effective premium, and offers detailed actuarial models and analyses of five old-age pension saving products used in practice.

This book provides a contemporary treatment of the problems related to anomalous diffusion and anomalous relaxation.

This volume is based on an international conference held at the Institute for Science Education (IPN) in Kiel in August 1985.

Lack of ability to think probabilistically makes one prone to a variety of irrational fears and vulnerable to scams designed to exploit probabilistic naivete, impairs decision making under uncertainty, facilitates the misinterpretation of statistical information, and precludes critical evaluation of likelihood claims.