Probability and statistics

How can a scalable and efficient quality management mechanism for cloud labor services be designed in a way that it delivers results with a well-defined level of quality to the requester?

This book provides the first comprehensive treatment of Benford's law, the surprising logarithmic distribution of significant digits discovered in the late nineteenth century.

In the United States, a rare disease is defined by the Orphan Drug Act as a disorder or condition that affects fewer than 200,000 persons.

This book describes the probability theory associated with frequently used statistical procedures and the relation between probability theory and statistical inference.

Managers need access to some statistical advice from time to time to help in solving business problems.

Das dreibändige Lehrbuch „Quantitative BWL“ stellt die theoretischen quantitativen Grundlagen der betrieblichen Entscheidungen und des marktwirtschaftlichen Umfelds dar.

The Credit Scoring Toolkit provides an all-encompassing view of the use of statistical models to assess retail credit risk and provide automated decisions.

30-Second Data Science covers 50 key elements in the field of data-gathering from basic to ethics, explained clearly and concisely.

Using a novel integration of mathematics and Python codes, this book illustrates the fundamental concepts that link probability, statistics, and machine learning, so that the reader can not only employ statistical and machine learning models using modern Python modules, but also understand their relative strengths and weaknesses.

This volume contains lecture notes from the coursesgiven by Vlad Bally and Rama Cont at the Barcelona Summer School on StochasticAnalysis (July 2012).

Renowned probability theorist Edward O.

If you place a large number of points randomly in the unit square, what is the distribution of the radius of the largest circle containing no points?

Nowadays bioinformaticians and geneticists are faced with myriad high-throughput data usually presenting the characteristics of uncertainty, high dimensionality and large complexity.

No detailed description available for "e;Causal Inference in R"e;.

The life and soul of any science are its problems.

This volume celebrates the many contributions which Gopinath Kallianpur has made to probability and statistics.

The subject theory is important in finance, economics, investment strategies, health sciences, environment, industrial engineering, etc.

Useful in the theoretical and empirical analysis of nonlinear time series data, semiparametric methods have received extensive attention in the economics and statistics communities over the past twenty years.

In all walks of life, at some point in time, we all use the process of problem solving.

Available in English for the first time, this classic and influential book by the late Kohei Ohtsu presents real examples of ships in motion under irregular ocean waves, how to understand the characteristics of fluctuations of stochastic phenomena through spectral analysis methods and statistical modeling.

This book discusses statistical process control (SPC) concepts, emphasizing the need to establish stability of work processes.

The R language provides a rich environment for working with data, especially data to be used for statistical modeling or graphics.

New developments in computer science, biology, mathematics and physics offer possibilities to obtain deeper understanding of growth and forms of organisms.

Machine Learning for Knowledge Discovery with R contains methodologies and examples for statistical modelling, inference, and prediction of data analysis.

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.

The three parts of this book on survey methodology combine an introduction to basic sampling theory, engaging presentation of topics that reflect current research trends, and informed discussion of the problems commonly encountered in survey practice.

R for Political Data Science: A Practical Guide is a handbook for political scientists new to R who want to learn the most useful and common ways to interpret and analyze political data.

This book is intended as a text for a two-quarter or two-semester post-calculus introduction to probability and mathematical statistics for undergraduate students in their junior or senior year, and also for graduate students in the quantitative sciences (e.

This book describes some approaches for developing the numerical models to efficiently predict the formation of extreme waves which can pose a threat to the safety of marine structures.

This book provides an overview of statistical concepts and basic methodology for the study of genetics of human traits and diseases.

Introducing the IBM SPSS Modeler, this book guides readers through data mining processes and presents relevant statistical methods.

Originally published in 1968, this book was intended to help those in health and welfare services as well as those whose policy decisions are influenced by the movement of statistical indices of health, to understand the purpose, derivation and meaning of these indices.

This book is devoted to Corrado Gini, father of the Italian statistical school.

Environmental Data Analysis is an introductory statistics textbook for environmental science.

This textbook teaches the basics of econometrics and focuses on the acquisition of methods and skills that are essential for any student to succeed in their studies, as well as for any practitioner interested in applying econometric techniques.

For a brief time in history, it was possible to imagine that a sufficiently advanced intellect could, given sufficient time and resources, in principle understand how to mathematically prove everything that was true.

Due to its data handling and modeling capabilities as well as its flexibility, R is becoming the most widely used software in bioinformatics.

Small noise is a good noise.

How to make simple sense of complex statistics--from the author of Numbers Rule Your WorldWe live in a world of Big Data--and it's getting bigger every day.

This book provides a direct and comprehensive introduction to theoretical and numerical concepts in the emerging field of optimal control of partial differential equations (PDEs) under uncertainty.

From the Preface.

Continuing the authors' multivolume project, this text considers the theory of distributions from an applied perspective, demonstrating how effective a combination of analytic and probabilistic methods can be for solving problems in the physical and engineering sciences.

When I wrote the book Quantitative Sociodynamics, it was an early attempt to make methods from statistical physics and complex systems theory fruitful for the modeling and understanding of social phenomena.

Using WinBUGS to implement Bayesian inferences of estimation and testing hypotheses, Bayesian Methods for Measures of Agreement presents useful methods for the design and analysis of agreement studies.

This volume contains original and refereed contributions from the tenth AMCTM Conference (www.