Upcoming Live R Workshops
No workshops scheduled at this time. Happy summer - see you in the fall!
Additional R Training Resources
Online Training: there are many excellent sources of R and RStudio instruction:
Guides and Cheat Sheets
RStudio Software at UVA
RStudio is freely available to download and use, but it is also installed in the Health Sciences Library's Carter Classroom (first level). It also is available through UVA Labs and Classrooms (locations with RStudio), as well as the UVA RemoteApps service.
Software Installations:
Prior to your first workshop session, please follow the instructions below to install necessary software and to set-up your physical space.
You’ll need the most recent version of R, 4.2.0. Download and install it for Windows or Mac. If you have a previous R installation, please check the version by opening R and typing R.version. If you have an older Mac OS, download the latest pkg file for your appropriate version of Mac OS.
Download and install RStudio Desktop version 2022.02.3
R and RStudio are separate downloads and installations. R is the underlying statistical computing environment, but using R alone is no fun. RStudio is a graphical integrated development environment that makes using R much easier. You need R installed before you install RStudio.
Lastly, we will need to install several core packages needed for most lessons. Launch RStudio (RStudio, not R itself). Ensure that you have internet access, then copy and paste the following 2 commands, one-at-a-time, into the Console panel (the lower-left panel, by default) and hit the Enter/Return key.
install.packages("tidyverse")
A few notes:
Check that you’ve installed everything correctly by closing and reopening RStudio and entering the following command at the console window.
library(tidyverse)
Don’t worry about any messages that look something like the following objects are masked from ...
, or Warning message: package ... was build under R version ...
Running the library(tidyverse) code may produce some notes or other output, but as long as you don’t get an error message, you’re good to go.
If you see output like this:
everything installed properly and is working. You are all set!
If you get a message that says something like: Error in library(somePackageName) : there is no package called 'somePackageName'
, then the required packages did not install correctly. Please do not hesitate to email the instructors prior to class if you are still having difficulty. In your email, please copy and paste what you typed in the console, and all of the output that streams by in the console.
Physical Space:
Because of these workshops’ online format, here are the best options for following along during class sessions. Most of the workshop consists of live coding, so the challenge will be how to simultaneously view the instructor’s screen and your screen given that the RStudio window is large and landscape format.
Please do not hesitate to email the instructors prior to class if you have questions about how best to set-up your workspace.
How to Unzip (aka Extract) Workshop Files for Windows
Files for our workshops are packaged together in a Zip file. You'll need to download AND fully unzip (aka extract) this file to get all the files for the session. Here's how:
Let us know if you have any questions!
Upcoming Live Excel Workshops
No live workshops scheduled at this time
Excel Workshop Materials
Handouts and the Excel practice file for our "Excel Bites" workshops:
Recorded Excel Workshops
Recordings of our "Excel Bites" (short, bite-sized Excel tutorials for beginners) are available below. For the accompanying handouts and exercises, see the links below under Workshop Materials.
Additional Excel Training Resources
Excel and other Microsoft training is available through these UVA subscriptions:
Upcoming Live SPSS Workshops
No live workshops scheduled at this time
SPSS Workshop Materials
Introduction to SPSS (2014) posted materials from a previous workshop by UVA Library Research Data Services)
Additional SPSS Training Resources
There are many excellent online resources for learning SPSS:
SPSS Software at UVA
There are several options for accessing SPSS at UVA for faculty, staff, students and sponsored accounts
See additional free, online workshops on data analysis, visualization, research computing and more from our on-Grounds partners:
University Library Research Data Services + Sciences and Research Computing Workshops
Training on data analysis, statistics, computation, and library resources. Fall 2022 topics will include: High Performance Computing, Information and Publishing, Qualitative Research, R, Python, Reproducibility, and Tableau.
University Library Scholar's Lab
Topics including geographic mapping, demographics, and more
Winter/Spring 2022
R Bootcamp
Introduction to R
Data Visualization in R with ggplot2
Data Preparation: taming wild data with R
Data Wrangling in R
Excel Bites: basic navigation
Excel Bites: formulas
Excel Bites: merging and separating data
Excel Bites: PivotTable
Excel Bites: PivotCharts
Fall 2021
Introduction to R
Data Visualization in R with ggplot2
Data Preparation: taming wild data with R
Data Wrangling in R
Essential Stats in R
Linear Models in R
Advanced Data Visualization in R
Dealing with Longitudinal Data in R
Excel Bites: basic navigation
Excel Bites: formulas
Excel Bites: merging and separating data
Excel Bites: PivotTable
Excel Bites: PivotCharts
Introduction to Qualtrics
Introduction to SPSS
Winter/Spring 2021
Data Visualization in R with ggplot2
Data Preparation: taming wild data with R
Data Wrangling in R
Excel Bites: basic navigation
Excel Bites: formulas
Excel Bites: merging and separating data
Excel Bites: PivotTable
Excel Bites: PivotCharts
Excel Bites: Macros
Introduction to Qualtrics
Introduction to R
Introduction to SPSS
R Bootcamp
Fall 2020
Data Visualization in R with ggplot2
Data Preparation: taming wild data with R
Excel Bites: basic navigation
Excel Bites: formulas
Excel Bites: merging and separating data
Excel Bites: PivotTable
Excel Bites: PivotCharts
Excel Bites: Macros
Introduction to Qualtrics
Introduction to R
Introduction to SPSS
Regression in R
Statistics in R
Summer 2020
Excel Bites: basic navigation
Excel Bites: formulas
Excel Bites: merging and separating data
Excel Bites: PivotTable
Excel Bites: PivotCharts
Winter/Spring 2020
Data Visualization in R with ggplot2
Data Preparation: taming wild data with R
Introduction to NCBI Resources
Introduction to Qualtrics
Introduction to R
Introduction to SPSS
R Code-In
Regression in R
Statistics in R
Fall 2019
Introduction to R
Data Visualization in R with ggplot2
Data Preparation: taming wild data with R
Power and Sample Size in R
Essential Skills for Data in Excel
Essential Statistics with R
Funding discovery workshop
Introduction to scientific image processing with Fiji/ImageJ
Automation of image processing with Fiji/ImageJ
Browsing Genes and Genomes with Ensembl and Ensembl Genomes
Introduction to QGIS
Introduction to Qualtrics
Regression in R
Qualitative Data Analysis and Introduction to Dedoose
Introduction to SPSS
Introduction to RNASeq
Machine Learning in R
Reproducible Research Using RMarkdown and GitHub
Moving R Programs to Rivanna
Managing R Libraries
Regression in R
Survival Analysis in R
Interactive Visualization with R using Shiny
Winter/Spring 2019
Introduction to R
Introduction to SPSS
Data Visualization in R with ggplot2
Data Preparation: Taming wild data with R
Essential Skills for Data in Excel
Essential Statistics with R
Power and Sample Size in R
Predictive Analytics with R
Managing R Libraries
Reproducible Research Using RMarkdown and GitHub
Interactive Visualization with R using Shiny
Regression in R
Introduction to RNASeq
Single cell RNASeq with Seurat
Introduction to QGIS
Qualitative Data Analysis and Introduction to Dedoose
Introduction to SAS
Funding Discovery Workshop
Introduction to Qualtrics
Introduction to scientific image processing with Fiji/ImageJ
Automation of image processing with Fiji/ImageJ
Introduction to NCBI Resources
Fall 2018
Introduction to R
Introduction to SPSS
Data Visualization in R with ggplot2
Data Preparation: Taming wild data with R
Essential Skills for Data in Excel
Essential Statistics with R
Introduction to QGIS
Introduction to Stata
Introduction to SAS
Funding Discovery Workshop
Introduction to Qualtrics
Introduction to scientific image processing with Fiji/ImageJ
SciFinder Skills Enhancement
Reaxys Medicinal Chemistry
Introduction to NCBI Resources
Regression in R
Automation of image processing with Fiji/ImageJ
Predictive Analytics with R
Building Shiny Web Applications in R
Winter/Spring 2018
Introduction to R
Introduction to SPSS
Data Manipulation in R with dplyr
Managing Your Spreadsheet Data
Interactive Visualization with R
Predictive Analytics with R
Funding Discovery Workshop
Survey Design with Analysis in Mind (Qualtrics)
Data Manipulation in R with dplyr
Essential Statistics with R
Using SPSS Syntax
Introduction to SAS
Building Shiny Web Applications in R
Data Visualization in R with ggplot2
Predictive Analytics with R
Essential Statistics with R
Using SPSS Syntax
Fall 2017
Coordinated under the UVA BioConnector branding, these workshops were led by SOM Research Computing, Health Sciences Library, Public Health Sciences, University Library, and Advanced Research Computing Services
Advanced Data Manipulation with R - 2017-10-03
Advanced Data Visualization with ggplot2 - 2017-10-30
Automated Image Analysis with ImageJ - 2017-10-19
Building Shiny Web Applications in R - 2017-04-18
Data cleansing in Python using Pandas and the Jupyter Notebook - 2017-10-09
Data visualization in Python - 2017-10-12
Essential Statistics with R - 2017-11-13
Introduction to Cloud Computing with AWS - 2017-09-26
Introduction to the Command Line - 2017-09-07
Introduction to Dedoose- 2017-10-31
Introduction to Docker Containers - 2017-10-31
Introduction to Git and GitHub 2017-09-22
Introduction to Ivy - 2017-09-19
Introduction to Matlab - 2017-11-07
Introduction to Python - 2017-09-05, 2017-09-11
Introduction to R - 2017-09-06, 2017-09-12
Introduction to Rivanna - 2017-09-21, 2017-11-01
Introduction to SAS - 2017-09-27
Introduction to Scientific Image Processing with Fiji/ImageJ, 2017-10-10
Introduction to SPSS - 2017-09-20
Organizing Your Spreadsheet Data - 2017-09-28, 2017-11-07
Overview of UVA Research Computing Resources - 2017-09-14
Power and Sample Size Analysis with R - 2017-10-12
Python Web apps using the Flask framework - 2017-10-23
R Package Development Tools - 2017-10-16
Reproducible Reporting with R and RMarkdown - 2017-11-6
Spring 2017
Coordinated under the UVA BioConnector branding, these workshops were led by SOM Research Computing, Health Sciences Library, Public Health Sciences, and the University Library
Advanced Data Manipulation with R - 2017-02-14
Advanced Data Visualization with R - 2017-02-21
Automated Image Analysis with ImageJ - 2017-03-29
Building Shiny Web Applications in R - 2017-04-18
Data cleansing in Python using Pandas and the Jupyter Notebook - 2017-03-15
Data visualization in Python using Matplotlib v. 2 and Bokeh - 2017-03-28
Essential Statistics with R - 2017-02-23
Introduction to Cloud Computing with AWS - 2017-04-04
Introduction to Python - 2017-02-09
Introduction to SAS - 2017-01-31
Introduction to the Command Line - 2017-01-26
Introduction to ArcGIS - 2017-03-27
Introduction to Dedoose - 2017-04-10
Introduction to SPSS - 2017-02-15
Managing Your Spreadsheet Data - 2017-03-14
Organizing Your Spreadsheet Data - 2017-01-24
Power and Sample Size Analysis with R - 2017-03-02
Python Web apps using the Flask framework - 2017-03-30
Quantitative analysis and visualization of medical images using Advanced Normalization Tools (ANTs) - 2017-04-19
R for Beginners - 2017-01-24
R for Beginners - 2017-02-02
Statistical Analysis with SAS - 2017-02-17
Survival Analysis in R with TCGA Data - 2017-03-31
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