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Doing Data Science in R

This approachable introduction to doing data science in R provides step-by-step advice on using the tools and statistical methods to carry;

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Introduction to Probabilistic and Statistical Methods with Examples in R

roots. It is intended as a comprehensive and largely self-contained introduction to probability and statistics for university students from;

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Introduction to Probabilistic and Statistical Methods with Examples in R

roots. It is intended as a comprehensive and largely self-contained introduction to probability and statistics for university students from;

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Statistical Computing with R

examples and R notes to help explain the R programming concepts. After an overview of computational statistics and an introduction to the R;

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R In Finance And Economics

This book provides an introduction to the statistical software R and its application with an empirical approach in finance and economics;

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Introduction to Multivariate Statistical Analysis in Chemometrics

Using formal descriptions, graphical illustrations, practical examples, and R software tools, Introduction to Multivariate Statistical;

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Biostatistics for Human Genetic Epidemiology

statistical foundations, before moving on to topics related human genetic epidemiology, with R codes illustrations for various;

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Biostatistics with R: An Introduction to Statistics Through Biological Data

Biostatistics with R is designed around the dynamic interplay among statistical methods, their applications in biology, and their;

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Expect the Unexpected

statistics.The examples are kept simple, so that the reader can learn quickly and see the usefulness of various statistical and probabilistic methods;

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Applied Probabilistic Calculus for Financial Engineering

necessary probabilistic and statistical foundations, before moving on to topics related to asset allocation and portfolio optimization with R codes;

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Probabilistic Inference and Statistical Methods in Network Analysis

Probabilistic Inference and Statistical Methods in Network Analysis examines various aspects of network analysis and analysis several;

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An introduction to mathematical statistics

. In An Introduction to Mathematical Statistics the authors describe key concepts from statistics and give a mathematical basis for important;

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An Introduction to Statistical Inference and Its Applications with R

Emphasizing concepts rather than recipes, An Introduction to Statistical Inference and Its Applications with R provides a clear exposition;

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An Introduction to Statistical Inference and Its Applications with R

Emphasizing concepts rather than recipes, An Introduction to Statistical Inference and Its Applications with R provides a clear exposition;

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Statistical Models in Earth Sciences

In this book, the author has given some introduction to the nature of complexities and processes within Earth Sciences and some of theses;

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Introdu To Statistical Computing

examples and exercises. * Provides answers to the exercises (using the statistical computing environment R); the corresponding source code;

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Introduction to R for Terrestrial Ecology: Basics of Numerical Analysis, Mapping, Statistical Tests and Advanced Application of R

This textbook covers R data analysis related to environmental science, starting with basic examples and proceeding up to advanced;

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Introduction to R for Terrestrial Ecology

This textbook covers R data analysis related to environmental science, starting with basic examples and proceeding up to advanced;

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An R Companion to Linear Statistical Models

course on regression and analysis of variance. For those who have never used R, the book begins with a self-contained introduction to R that lays;

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An R Companion to Linear Statistical Models

course on regression and analysis of variance. For those who have never used R, the book begins with a self-contained introduction to R that lays;

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Probabilistic Safety Assessment for Optimum Nuclear Power Plant Life Management (PLiM)

one reviews probabilistic methods for predicting the reliability of equipment. Following an introduction to key terminology, concepts and;

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An introduction to mathematical statistics

. In An Introduction to Mathematical Statistics the authors describe key concepts from statistics and give a mathematical basis for important;

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Statistical Computing with R, Second Edition

in computational statistics or for self-study, Statistical Computing with R, Second Edition provides a balanced, accessible introduction to computational;

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A First Course in Bayesian Statistical Methods

. Numerous examples with R-code that can be run as-is allow the reader to perform the data analyses themselves. The development of Monte;

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A First Course in Bayesian Statistical Methods

. Numerous examples with R-code that can be run as-is allow the reader to perform the data analyses themselves. The development of Monte;

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Introductory Statistics with R

This book provides an elementary-level introduction to R, targeting both non-statistician scientists in various fields and students;

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Statistics for Data Scientists

students. It uniquely combines a hands-on approach to data analysis - supported by numerous real data examples and reusable [R] code - with a;

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