Applied Multivariate Statistics in R by Jonathan Bakker (.ePUB)+
File Size: 23.4 MB
Applied Multivariate Statistics in R by Jonathan Bakker
Requirements: .ePUB, .PDF reader, 23.4 MB | True PDF, True EPUB
Overview: Applied multivariate statistics, with an emphasis on worked examples from ecology. Used as the textbook for SEFS 502 (Analytical Techniques for Community Ecology) at the University of Washington. R is an open source statistical language and is extremely versatile and customizable. Scripting is one of the powerful aspects of R that distinguishes it from point-and-click statistical software. When a script is clearly written, it is easy to re-run an analysis as desired – for example, after a data entry error is fixed or if you decide to focus on a particular subset of the data. To capitalize on this ability, it is necessary to be able to manipulate your data in R. New users often want to export their data to Excel, manipulate it there, and re-import it into R. Resist this urge. Working in R helps you avoid errors that can creep in in Excel – such as calculating an average over the wrong range of cells – and that are extremely difficult to detect. A script is simply a text file containing the code used (actions taken), along with comments explaining why those actions were taken. I save these files with a ‘.R’ suffix to distinguish them from other text files. Scripts can be created within RStudio’s editor panel (my preference) but could also be created in R’s Editor or even in a simple text editor like WordPad. Commands have to be copied and pasted into R for execution.
Genre: Non-Fiction > Tech & Devices
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