From a2c14981252d25b815e796daa3caa20d05e21d34 Mon Sep 17 00:00:00 2001 From: Sarah Young Date: Tue, 9 Jan 2024 12:29:12 -0500 Subject: [PATCH] Add files via upload --- content/introR.md | 53 +++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 53 insertions(+) create mode 100644 content/introR.md diff --git a/content/introR.md b/content/introR.md new file mode 100644 index 0000000..21637bf --- /dev/null +++ b/content/introR.md @@ -0,0 +1,53 @@ +--- +layout: default +title: Introduction to R Getting started with R and RStudio +has_children: true +nav_order: 2 +--- + +# Introduction to R: Getting started with R and RStudio +Hosted by the [Carnegie Mellon University (CMU) Libraries](https://www.library.cmu.edu/) + +## About this Workshop + +This 2-part introductory workshop aims to teach basic concepts, skills, and tools for working with data in R so that you can get more done in less time, and apply concepts of reproducibility to your research. This is an introduction to R designed for participants with no programming experience. Part 1 of the workshop covers basic information about R syntax and the RStudio interface, including installing packages and working with vectors. Part 2 will cover importing CSV files, working with dataframes, how to deal with factors, how to add/remove rows and columns using the popular dplyr package, and how to calculate summary statistics from a data frame. Taking Part 1 and Part 2 is encouraged, but optional. + +Learners should bring a laptop and should already have installed R and RStudio on their computer. Installation and set-up instructions, as well as a detailed curriculum for the workshop can be downloaded here. +____ +### Presenters +Sarah Young +Principal Librarian +Office: 109G, Hunt Library +[sarahy@andrew.cmu.edu](mailto:sarahy@andrew.cmu.edu) + +### Goals of this Workshop +#### Part 1 +* Describe the different panes in the RStudio environment and how they are used when coding in R. +* Run lines of R code from a script file to the console. +* Create and store new objects in R. +* Find help information for functions. +* Use functions in R with appropriate syntax and arguments. +* Define, create and manipulate vectors in R. + + +#### Part 2 +* Install packages and load libraries in R. +* Import a dataset and use tidyverse functions to explore dataset attributes. +* Create subsets of dataframes. +* Work with categorical variables in R. +* Use the dplyr package to select columns and filter rows. +* Use the dplyr package to perform various operations on a dataframe such as creating new variables, splitting and combining data, and summarizing data. +* Use pipes in R to string together a series of steps. +* Export a data set from R Studio. + + +## Schedule TBD + + +### Slides + *Click on the slides then press CTRL+Shift+F for full screen* + +### Acknowledgements + +The lesson materials and slides for this workshop were largely adapted from the [Data Carpentries lesson "R for Social Scientists"](https://datacarpentry.org/r-socialsci/). Content was adapted and reformatted for the CMU Libraries workshop series by Patrick Campbell. +