Reliable data analysis lies at the heart of scientific research, helping you to figure out what your data is really telling you. Yet the analysis of data can be a stumbling block for even the most experienced researcher - and can be a particularly daunting prospect when analyzin…
Haider offers informative, jargon-free coverage of basic theory and technique, backed with plenty of vivid examples and hands-on practice opportunities. Everything is software and platform agnostic, so you can learn data science whether you work with R, Stata, SPSS, or SAS. She …
Become an expert in Bayesian Machine Learning methods using R and apply them to solve real-world big data problems About This Book Understand the principles of Bayesian Inference with less mathematical equations Learn state-of-the art Machine Learning methods Familiarize yoursel…
A Hands-On Approach to Understanding and Using Actuarial Models Computational Actuarial Science with R provides an introduction to the computational aspects of actuarial science. Using simple R code, the book helps you understand the algorithms involved in actuarial computations…
This book is an easy-to-follow, stepwise guide to handle real life Bioinformatics problems. Each recipe comes with a detailed explanation to the solution steps. A systematic approach, coupled with lots of illustrations, tips, and tricks will help you as a reader grasp even the t…
Hugely successful and popular text presenting an extensive and comprehensive guide for all R users The R language is recognized as one of the most powerful and flexible statistical software packages, enabling users to apply many statistical techniques that would be impossible wi…
An Up-to-Date, All-in-One Resource for Using SAS and R to Perform Frequent TasksThe first edition of this popular guide provided a path between SAS and R using an easy-to-understand, dictionary-like approach. Retaining the same accessible format, SAS and R: Data Management, Stat…
R is a popular and growing open source statistical analysis and graphics environment as well as a programming language and platform. You'll be able to navigate the R system, enter and import data, manipulate datasets, calculate summary statistics, create statistical plots and cu…
R is a popular and growing open source statistical analysis and graphics environment as well as a programming language and platform. You'll be able to navigate the R system, enter and import data, manipulate datasets, calculate summary statistics, create statistical plots and cu…
R is a popular and growing open source statistical analysis and graphics environment as well as a programming language and platform. You'll be able to navigate the R system, enter and import data, manipulate datasets, calculate summary statistics, create statistical plots and cu…
A Practical Guide to Implementing Nonparametric and Rank-Based Procedures Nonparametric Statistical Methods Using R covers traditional nonparametric methods and rank-based analyses, including estimation and inference for models ranging from simple location models to general line…
Suitable for both beginners and advanced users, this book shows you how to write reports in simple languages such as Markdown. The reports range from homework, projects, exams, books, blogs, and web pages to any documents related to statistical graphics, computing, and data anal…
by Xie, Yihui
fromChapman & Hall/CRC the R series (CRC Press)
IntroductionReproducible ResearchLiteratureGood and Bad PracticesBarriersA First LookSetupMinimal ExamplesQuick Reporting Extracting R Code Editors RStudio LYX Emacs/ESS Other Editors Document FormatsInput Syntax Document Formats Output Renderers R Scripts Text OutputInline Outp…
"Suitable for both beginners and advanced users, this book shows you how to write reports in simple languages such as Markdown. The reports range from homework, projects, exams, books, blogs, and web pages to any documents related to statistical graphics, computing, and data ana…
