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Geocomputation with R

Geocomputation with R

1st Edition

Featured

Robin Lovelace, Jakub Nowosad, Jannes Muenchow
March 25, 2019

Geocomputation with R is for people who want to analyze, visualize and model geographic data with open source software. It is based on R, a statistical programming language that has powerful data processing, visualization, and geospatial capabilities. The book equips you with the knowledge and skill...

A Concise Introduction to Machine Learning

A Concise Introduction to Machine Learning

1st Edition

A.C. Faul
August 12, 2019

The emphasis of the book is on the question of Why – only if why an algorithm is successful is understood, can it be properly applied, and the results trusted. Algorithms are often taught side by side without showing the similarities and differences between them. This book addresses the...

Sturge's Statistical and Thermal Physics, Second Edition

Sturge's Statistical and Thermal Physics, Second Edition

2nd Edition

Jeffrey Olafsen
July 19, 2019

The original work by M.D. Sturge has been updated and expanded to include new chapters covering non-equilibrium and biological systems. This second edition re-organizes the material in a more natural manner into four parts that continues to assume no previous knowledge of thermodynamics. The four...

Probability and Statistics for Data Science: Math + R + Data

Probability and Statistics for Data Science: Math + R + Data

1st Edition

Norman Matloff
June 20, 2019

Probability and Statistics for Data Science: Math + R + Data covers "math stat"—distributions, expected value, estimation etc.—but takes the phrase "Data Science" in the title quite seriously: * Real datasets are used extensively. * All data analysis is supported by R coding. * Includes...

Probability and Statistics for Computer Scientists, Third Edition

Probability and Statistics for Computer Scientists, Third Edition

3rd Edition

Michael Baron
June 14, 2019

Praise for the Second Edition: "The author has done his homework on the statistical tools needed for the particular challenges computer scientists encounter... [He] has taken great care to select examples that are interesting and practical for computer scientists. ... The content is illustrated...

Bringing Bayesian Models to Life

Bringing Bayesian Models to Life

1st Edition

Mevin B. Hooten, Trevor J. Hefley
June 11, 2019

Bringing Bayesian Models to Life empowers the reader to extend, enhance, and implement statistical models for ecological and environmental data analysis. We open the black box and show the reader how to connect modern statistical models to computer algorithms. These algorithms allow the user to fit...

Statistics for Business

Statistics for Business

1st Edition

Perumal Mariappan
June 04, 2019

Statistics for Business is meant as a textbook for students in business, computer science, bioengineering, environmental technology, and mathematics. In recent years, business statistics is used widely for decision making in business endeavours. It emphasizes statistical applications, statistical...

Time Series: A Data Analysis Approach Using R

Time Series: A Data Analysis Approach Using R

1st Edition

Robert Shumway, David Stoffer
May 21, 2019

The goals of this text are to develop the skills and an appreciation for the richness and versatility of modern time series analysis as a tool for analyzing dependent data. A useful feature of the presentation is the inclusion of nontrivial data sets illustrating the richness of potential...

Textbook of Clinical Trials in Oncology: A Statistical Perspective

Textbook of Clinical Trials in Oncology: A Statistical Perspective

1st Edition

Susan Halabi, Stefan Michiels
May 16, 2019

There is an increasing need for educational resources for statisticians and investigators. Reflecting this, the goal of this book is to provide readers with a sound foundation in the statistical design, conduct, and analysis of clinical trials. Furthermore, it is intended as a guide for...

The Analysis of Time Series: An Introduction with R

The Analysis of Time Series: An Introduction with R

7th Edition

Chris Chatfield, Haipeng Xing
May 09, 2019

This new edition of this classic title, now in its seventh edition, presents a balanced and comprehensive introduction to the theory, implementation, and practice of time series analysis. The book covers a wide range of topics, including ARIMA models, forecasting methods, spectral analysis, linear...

R For College Mathematics and Statistics

R For College Mathematics and Statistics

1st Edition

Thomas Pfaff
April 22, 2019

R for College Mathematics and Statistics encourages the use of R in mathematics and statistics courses. Instructors are no longer limited to ``nice'' functions in calculus classes. They can require reports and homework with graphs. They can do simulations and experiments. R can be useful for...

Bayesian Statistical Methods

Bayesian Statistical Methods

1st Edition

Brian J. Reich, Sujit K. Ghosh
April 16, 2019

Bayesian Statistical Methods provides data scientists with the foundational and computational tools needed to carry out a Bayesian analysis. This book focuses on Bayesian methods applied routinely in practice including multiple linear regression, mixed effects models and generalized linear models (...

Sampling: Design and Analysis

Sampling: Design and Analysis

2nd Edition

Sharon L. Lohr
April 09, 2019

This edition is a reprint of the second edition published by Cengage Learning, Inc. Reprinted with permission. What is the unemployment rate? How many adults have high blood pressure? What is the total area of land planted with soybeans? Sampling: Design and Analysis tells you how to design and...

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