Add files via upload

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 <a href='https://github.com/rootsandberries' target='_blank'><img src='../content/img/GitHub-Mark-custom.svg' style='width:15px; padding:0; border:none !important;'></a>  
+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  
+<iframe src="https://docs.google.com/presentation/d/e/2PACX-1vTtce_WhgJuaF3PX5Zo3YrR7rUS25rpbBIWW0cZjo39Zn5Bk7qmMpOultF2EXTxcrT4JcFqiDtKdNdG/embed?start=false&loop=false&delayms=60000" frameborder="0" width="960" height="569" allowfullscreen="true" mozallowfullscreen="true" webkitallowfullscreen="true"></iframe>  *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.  
+