![]() Kidder 28 (Mac); Kidder 33 (Windows); Milne 130 (Windows); Milne 150 (Windows. At OSU Cascades, Adobe Creative Cloud is installed on 2 machines in the open lab that. Mamp install for mac youtube download. R (open source statistics package), ✓, ✓, ✓. R Studio, ✓, ✓, ✓. On This Page • • • Schedule of Classes Terms and Abbreviations Avail = Remaining seats available Baccalaureate / WIC Courses All baccalaureate core classes in the Schedule of Classes have an asterisk '*' in the title. The course description also contains the note, '(Bacc Core Course)'. All writing intensive course classes (WIC) have a carat ^ in the title. The course description also contains the note, '(Writing Intensive Course)'. Introduction The R programming language is widely used for the analysis of statistical data sets. RStudio So, what is R and RStudio? ![]() According to: • 'R is a language and environment for statistical computing and graphics.' • 'R provides a wide variety of statistical (linear and nonlinear modeling, classical statistical tests, time-series analysis, classification, clustering), and graphical techniques, and is highly extensible.' • 'One of R’s strengths is the ease with which well-designed publication-quality plots can be produced, including mathematical symbols and formulae where needed.' • 'R is available as Free Software under the terms of the Free Software Foundation’s GNU General Public License in source code form. It compiles and runs on a wide variety of UNIX platforms and similar systems (including FreeBSD and Linux), Windows and MacOS.' R Basics R Programming Course This R programming course introduces the language, covering topics such as: • R basics • Basic data types (e.g. Integers, numerics, characters, vectors, lists, matrices, and data frames) • Importing and manipulating data (in particular, vector and data-frame indexing) • Control flow (loops, conditionals, and functions) • And good practices for producing readable, reusable, and efficient R code This r language online course is designed for students or researchers with no previous experience in R, and those with some experience but who would like an overview of R fundamentals to gain additional independence. Kevin Weitemier holds a B.A. In Biology from Colorado College, a M.S. In Biology from Portland State University, and a Ph.D. From the Department of Botany & Plant Pathology at Oregon State University. He currently serves as a bioinformatician and trainer for the OSU Center for Genome Research and Biocomputing, where he provides analytical support for research on and off campus and supports training opportunities in computational and bioinformatic analysis. His research centers around plant systematics and genomics, emphasizing population genomics and the process of speciation.
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