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Based on their extensive experience with teaching R and statistics to applied scientists, the authors provide a beginner's guide to R. The text covers how to download and install R, import and manage data, elementary plotting, an introduction to functions, advanced plotting, and common beginner mistakes.
The science of sound, or acoustics, studies all types of sounds and therefore covers a wide range of scientific disciplines, from pure to applied acoustics.
Introducing Monte Carlo Methods with R covers the main tools used in statistical simulation from a programmer's point of view, explaining the R implementation of each simulation technique and providing the output for better understanding and comparison.
Business Analytics for Managers helps readers extract knowledge and actionable insight from real business data. The text emphasizes data-driven thinking and provides a quick-start guide to one of the most powerful software solutions available.
Presenting a practitioner's guide to capabilities and best practices of quality control systems using the R programming language, this volume emphasizes accessibility and ease-of-use through detailed explanations of R code as well as standard statistical methodologies.
This textbook offers an easy-to-follow, practical guide to modern data analysis using the programming language R.
Today, information technology plays a pivotal role in financial control and audit: most financial data is now digitally recorded and dispersed among servers, clouds and networks over which the audited firm has no control.
Provides simple explanations of the important concepts in population and community ecology. Provides R code throughout, to illustrate model development and analysis, as well as appendix introducing the R language. Interweaves ecological content and code so that either stands alone.
This volume provides user-friendly software and a GUI package to assist with microarray data analysis in early drug development. Each methodological issue is illustrated using real-world examples of early drug development dose-response microarray experiments.
Applied Spatial Data Analysis with R, second edition, is divided into two basic parts, the first presenting R packages, functions, classes and methods for handling spatial data.
In addition to using real-life data sets to demonstrate each method, the book also reports each method in three parts-- first describing when and why to apply it, then how to compute the method in R, and finally how to present, visualize, and interpret the results.
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