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Statistical Computing Environments for Social Research

sciences and statistics, Statistical Computing Environments for Social Research describes seven statistical computing environments--APL2STAT, GAUSS;

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Statistical Computing Environments for Social Research

sciences and statistics, Statistical Computing Environments for Social Research describes seven statistical computing environments--APL2STAT, GAUSS;

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Statistical Computing

of statistical computing. ---Mathematics of Computation . The text is highly readable and well illustrated with examples. The reader who intends to take;

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Elements of Statistical Computing

development of statistical theory. At the same time, the computational methods used in statistical work span much of computer science. Elements;

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Introdu To Statistical Computing

A comprehensive introduction to sampling-based methods in statistical computing The use of computers in mathematics and statistics has;

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Statistical Computing with R

Computational statistics and statistical computing are two areas that employ computational, graphical, and numerical approaches to solve;

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Advanced Computing Technologies and Applications

-generation computing, the book focuses on recent developments in intelligent computing, such as linguistic computing, statistical computing, data;

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Advanced Computing Technologies and Applications

-generation computing, the book focuses on recent developments in intelligent computing, such as linguistic computing, statistical computing, data;

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Numerical Issues In Statistical Computing For The Social Scientist

At last-a social scientist's guide through the pitfalls of modern statistical computing Addressing the current deficiency in the literature;

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Handbook of Parallel Computing and Statistics

, and application of algorithms for solving statistical problems. After a brief introduction to parallel computing, the book explores the;

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Statistical Computing with R, Second Edition

statistical computing are two areas within statistics that may be broadly described as computational, graphical, and numerical approaches to solving;

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Basic Course In Statistics

scatter plots; to simulate probability models in order to illustrate probability and statistical theory. Explains how to tackle computing;

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Statistical Computing in Nuclear Imaging

Statistical Computing in Nuclear Imaging introduces aspects of Bayesian computing in nuclear imaging. The book provides an introduction to;

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Statistical Computing in Nuclear Imaging

Statistical Computing in Nuclear Imaging introduces aspects of Bayesian computing in nuclear imaging. The book provides an introduction to;

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Biostatistics

The emergence of high-speed computing has facilitated the development of many exciting statistical and mathematical methods in the last 25;

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Reliability and Statistical Computing

between theory and practice and explores new research challenges in reliability and statistical computing. The book consists of 18;

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Reliability and Statistical Computing

between theory and practice and explores new research challenges in reliability and statistical computing. The book consists of 18;

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Basic Statistics for Business and Economics

Offers the useful topics of statistical tools and methods delivered in a student friendly, step-by-step format. This title illustrates;

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Lectures On Quantum Computing, Thermodynamics And Statistical Physics

This book is a collection of lecture notes from the Symposium on Quantum Computing, Thermodynamics, and Statistical Physics, held at Kinki;

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Interface Between Quantum Information And Statistical Physics

This book is a collection of contributions to the Symposium on Interface between Quantum Information and Statistical Physics held at Kinki;

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Distribution-Free Statistical Methods, Second Edition

Distribution-free statistical methods enable users to make statistical inferences with minimum assumptions about the population in question;

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Distribution-free Statistical Methods

Distribution-free statistical methods enable users to make statistical inferences with minimum assumptions about the population;

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An R Companion to Applied Regression

An R Companion to Applied Regression is a broad introduction to the R statistical computing environment in the context of applied;

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Symbolic Computation for Statistical Inference

Over recent years, developments in statistical computing have freed statisticians from the burden of calculation and have made possible new;

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Intelligent Systems

, internet security, pattern recognition, predictive analytics applications in healthcare, sensor networks and social sensing and statistical;

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Advances in Computing Communication and Control

information and statistical computing, learning algorithms, system security, virtual reality, cloud computing, service oriented architecture;

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Dynamic Documents with R and knitr, Second Edition

Edition makes writing statistical reports easier by integrating computing directly with reporting. Reports range from homework, projects, exams;

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