Workshops

We offer training on data analysis, statistics, and computation (Data Workshops) and on Library resources and methods (Research Workshops). All are welcome (and they’re free)! See the full list of RDS workshops
and find workshops offered by our colleagues!

Spring 2019 Data Workshops Click date to register Time Location
R: Introduction to R (Jenn Huck) Tue 1/22 10:00 – 12:00 Brown 133
This workshop provides a gentle introduction to R and RStudio. R is a free, open-source software environment and programming language designed specifically for statistical analysis; RStudio is a free, open source integrated development environment (IDE) for R that provides a friendly interface for viewing graphs, data tables, R code, and output all at the same time. In this hands-on workshop we’ll get started navigating R with RStudio, loading libraries, and importing data. We’ll do some basic data manipulation, exploration, and analysis, and begin creating plots and graphics. And we’ll cover some key practices and shortcuts for using R effectively and helpful resources for learning more.

Workshop Materials


Python: Introduction to Python (Erich Purpur) Tue 1/22 1:00 – 2:30 Brown 133
This introductory workshop covers the fundamentals of Python, a popular general purpose, high level programming language. We’ll learn how to get started, the basic grammar of the python programming language, and the basics of writing readable code and running Python scripts. We’ll talk about how to load and use packages and learn about variables and built-in data types. This will be a hands-on experience with exercises throughout and plenty of time to get your hands dirty.

Workshop Materials


R: Data Preparation/Tidy Data in R (Michele Claibourn) Tue 1/29 10:00 – 12:00 Brown 133
Before analyzing data, we spend considerable effort wrangling the data into an analyzable form — creating and recoding variables, merging data sets, filtering and aggregating data, reshaping and more. In this workshop, we’ll learn about data preparation using dplyr, a library defining a grammar of data manipulation, and tidyr, a library for reshaping and tidying data. We’ll also cover working with data types like factors and dates and using conditional logic. This workshop assumes basic experience using R at the level of our Intro to R workshop.

Workshop Materials


Introduction to the Command Line (Aycan Katitas) Wed 1/30 12:30 – 2:00 Brown 133
This workshop provides an introduction to the command-line interface. We’ll learn how to use commands to perform basic operations in the terminal — creating or navigating directories, listing and displaying files, moving or copying files — as well as searching files, managing file permissions, and creating symbolic links. Working in the command line, we can combine existing programs, automate repetitive tasks, and connect to remote resources.

Workshop Materials


Qualitative Data Analysis + Intro to Dedoose (Christine Slaughter) Thu 1/31 10:00 – 12:00 Brown 133
In this workshop, we’ll explore principles of qualitative analysis, including coding, discerning patterns, relevant software, and how to build an argument using your data. We’ll learn how to use Dedoose, an online qualitative data analysis tool, to analyze and visualize a variety of information, including text articles, audio, video, and still images.

Workshop Materials


Intro to QGIS (Erich Purpur) Mon 2/4 10:00 – 11:30 Brown 133
This workshop will be a hands-on introduction to QGIS, a widely used open source Geographic Information Systems program. We will talk briefly about background concepts, compare QGIS with ArcGIS. We’ll use some sample data and walk through some of the basic tools and operations. Lastly, you’ll learn how to help yourself in the future.

Workshop Materials


R: (Exploratory) Data Visualization in R (Clay Ford) Tue 2/5 10:00 – 12:00 Brown 133
Exploring our data with graphs allows us to visualize relationships, spot unusual observations, or find unexpected patterns. In this workshop we introduce how to effectively use the ggplot2 package to explore and visualize data in R. With its consistent syntax and layered approach to making graphics, ggplot2 has revolutionized data visualization. What previously would have required hours of tedious programming can now be accomplished in a few lines of ggplot2 code. This workshop will introduce the logic behind ggplot2, how to use ggplot2 to explore your data, and how to customize and polish ggplot2 graphs. This workshop assumes basic experience using R at the level of our Intro to R workshop and familiarity with the dplyr package.

Download workshop materials


Introduction to Data Visualization with Tableau Part 1 (Nancy Kechner) Wed 2/6 10:00 – 12:00 Brown 133
This workshop, part 1 of a series, introduces basic principles and processes of good data visualization. We’ll discuss visual perception, including use of color and dimensions, along with best practices for making graphics readable and insightful. We’ll review data types and the appropriate dimensions and visualizations to effectively represent different types of data. And we’ll introduce Tableau Public as a tool to make beautiful and interactive data visualizations using hands-on examples.

Workshop Materials


R: Linear Modeling in R (Michele Claibourn) Tue 2/12 10:00 – 12:00 Brown 133
The linear model is one of the most commonly-used statistical models. Also called the regression model or the ordinary linear regression, linear modeling is the foundation for more complex general linear models like logit or count models, mixed-effects models, and structural equation models. So it’s a good model to understand. This workshop will cover to use R to fit and analyze linear models. Through hands-on examples, we’ll talk about interpretation of model output and checking model assumptions. We’ll also explore dummy variables, interactions, and variable transformations. While the workshop will assume you’ve met a regression model before, it can serve as a refresher for forgotten statistics! This workshop also assumes basic experience using R and familiarity with the tidyverse libraries, or successful completion of our Intro to R, Data Preparation in R, and Data Visualization in R workshops.

Workshop Materials


Introduction to Data Visualization with Tableau Part 2 (Nancy Kechner) Wed 2/13 10:00 – 12:00 Brown 133
In this workshop, part 2 of a series, we’ll continue to work within Tableau to create beautiful and interactive data visualizations. We’ll review a variety of visualization approaches and chart types — bar charts, scatterplots, line graphs, histograms, and heat maps — and discuss when they are most appropriate, how to get the most out of them, and how to implement them in Tableau. We’ll work through a variety of hands-on examples, so bring your laptops.

Workshop Materials


Python: Introduction to Python (Pete Alonzi) Wed 2/13 2:00 – 4:00 Brown 133
This introductory workshop covers the fundamentals of Python, a popular general purpose, high level programming language. We’ll learn how to get started, the basic grammar of the python programming language, and the basics of writing readable code and running Python scripts. We’ll talk about how to load and use packages and learn about variables and built-in data types. This will be a hands-on experience with exercises throughout and plenty of time to get your hands dirty.

Access workshop materials


Census Basics (Jenn Huck) Thu 2/14 10:00 – 11:00 Brown 133
In this workshop, we’ll learn about the available Census surveys (there’s more than one!), talk about the strengths and limitations of each, and understand what types of questions each can best address. We’ll go over hte multiple Census geographies, what they represent, and how the fit together. And we’ll look at where and how Census data can be accessed, including easy-to-download sources as well as more advanced options. Finally, we’ll discuss standard errors in the frequently-used American Community Survey data, what they are, and how to use and interpret them appropriately.

https://guides.lib.virginia.edu/censusWorkshop


R: Visualizing Models, Communicating Results in R (Clay Ford) Tue 2/19 10:00 – 12:00 Brown 133
The statistical model is often the workhorse method for quantifying or establishing relationships in experimental or observational data. However the results of modeling are often tables of numbers that can defy intuition. In this workshop we introduce approaches to visualizing models in R to help explain how they work, what they mean and how certain we can be of their predictions. We’ll also present ways to help format modeling output for use in LaTeX or R Markdown reports. Speaking of R Markdown, that’s RStudio’s platform for creating documents that combine R code, output, graphs and exposition. We’ll get you up and running with R Markdown as well! This workshop assumes experience with R and linear modeling at the level of our Linear Modeling in R workshop.

Download workshop materials


Data in Excel (Nancy Kechner) Wed 2/20 rescheduled to Wed 2/27 10:00 – 12:00 Brown 133
Excel is a widely-used spreadsheet program and business application. It can be a powerful tool for organizing and representing data. In this workshop we’ll learn about using Excel for data preparation, analysis, and visualization. This hands-on session will cover the basics of Excel, from entering data, exploring data, generating new variables with formulas, creating charts and graphs, and aggregating and summarizing data with pivot tables.


Python: Data Preparation in Python (Pete Alonzi) Wed 2/20 rescheduled to Wed 2/27 2:00 – 4:00 Brown 133
Before analyzing data, we spend considerable effort wrangling the data into an analyzable form — creating and recoding variables, merging data sets, filtering and aggregating data, reshaping and more. In this workshop, we’ll learn about data preparation using Python3 and pandas, “providing fast, flexible, and expressive data structures designed to make working with structured (tabular, multidimensional, potentially heterogeneous) and time series data both easy and intuitive.” We’ll also cover working with data types like factors and dates and using conditional logic. This workshop assumes basic experience using Python3 at the level of our Intro to Python workshop.

Access workshop materials


R: Interactive Web Apps in R with shiny (Clay Ford) Tue 2/26 10:00 – 12:00 Brown 133
Imagine presenting your research using a web application that allows a user to interact with your statistical model and see how it behaves given various inputs. Or think about being able to teach a statistical concept such as correlation where you can interactively change the correlation coefficient and see the resulting scatterplot of a linear relationship. The shiny package makes applications like this surprisingly easy to create in R. In this workshop we’ll get up and running with shiny and provide several examples that you can adapt to your own research and courses. As you’ll find out, you don’t have to be a web developer to create web applications in R! And thanks to RStudio, these applications can be run locally on your computer or shared with colleagues or students as R scripts. This workshop assumes experience with R and linear modeling at the level of our Linear Modeling in R and Visualizing Models workshops.

Workshop Materials


Introduction to Git and GitHub (Ricky Patterson) Tue 2/26rescheduled to Tue 3/5 12:00 – 2:30 Brown 133
This workshop introduces version control using git through both GitHub and GitLab, which are free and open source platforms for building projects collaboratively. We’ll learn the basics of git repositories and commits. We’ll cover how to fork a repository on GitHub/GitLab to your account, clone the repository to your local machine, and point it to the source repository. And we’ll practice GitHub/GitLab workflows like fetching and merging changes from the source, making changes and commits locally, pushing to GitHub/GitLab, and making pull requests. Please bring your laptops. The use of GitHub and GitLab both require user accounts so please set yours up before the workshop at github.com and gitlab.com

Workshop Materials


Python: Machine Learning in Python (Pete Alonzi) Wed 2/27 rescheduled to Wed 3/20 2:00 – 4:00 Brown 133
This workshops highlights fundamentals of machine learning using the python package scikit-learn. We will work through the steps of a machine learning example and explain the core concepts as we go; the session will be hands on, so bring your laptops. This workshop assumes basic experience working with data in Python at the level of our Introduction to Python or Data Preparation in Python workshops.

Access workshop materials


Qualtrics for Survey Research (Nancy Kechner) Wed 3/6 10:00 – 12:00 Brown 133
This introductory workshop will cover everything you need to know to start developing and distributing surveys in Qualtrics, a powerful web-based survey tool available to all students, staff, and faculty at UVa. We’ll cover common survey question types, required questions, and content validation. We’ll learn about skips and display logic, randomization, and survey flow. Finally, we’ll look at different options for distributing surveys and getting reports out of Qualtrics.


Research Data Management Fundamentals (Bill Corey) Tue 3/19 2:00 – 3:30 Brown 133
This workshop provides an overview of data management topics and practices, including file organization and formats, creating documentation and metadata, data security and backups, and data publishing and sharing. The emphasis is on strategies researchers can implement to make their data more findable, accessible, interoperable, and reusable — for themselves or others. We’ll also cover responsible data reuse, including citation, credit, and copyright.


Spring 2019 Research Workshops Click date to register Time Location
Funding Discovery Tools (Ricky Patterson) Wed 1/30 2:00 – 3:00 Brown 133
Funding discovery databases help researchers identify opportunities from public and private funders. UVa has access to two discovery tools licensed by the Vice Provost of Research Office, Pivot and GrantForward. These tools allow all UVa faculty, students and staff to search for funding and set up email search alerts based on a researcher’s area of interest. In this workshop, attendees will learn how to create an account, search the databases, share funding opportunities with others, as well as save search strategies for email alerts regarding new opportunities. We will also briefly explore the features of the Foundation Directory Online. Please bring a laptop for use during this hands-on workshop.

Workshop Materials


Introduction to Zotero (Maggie Nunley) Fri 2/8 2:00 – 3:30 Brown 133
Zotero is an open source tool that can help you keep track of citations while you search, create citations while you write, generate a formatted bibliography, and organize references and information. In this hands-on workshop we will cover a comprehensive introduction to the main features of Zotero including initial set-up, importing citations, saving document files, and creating bibliographies in a number of formats.

 

 


Advanced Zotero (Jeremy Garritano) Fri 2/15 2:00 – 3:30 Brown 133
This workshop will focus on advanced features in Zotero, an open source tool citation management tool. We’ll look at collaboration features (Collections, Groups), tools for advanced organization (tags, metadata) of your library, customization options, and sharing of useful plugins (such as PDF annotators). This workshop assumes you have Zotero installed and are familiar with importing citations/documents and creating simple bibliographies.

Workshop materials


Introduction to LaTeX/Overleaf (Ricky Patterson) Tue 2/19 2:00 – 3:30 Brown 133
LaTeX is a powerful (and free) document typesetting program, widely used in a number of academic disciplines for compiling professional research papers, articles, dissertations, presentations, letters, and books. It is especially useful for the creation and integration of mathematical formulae, tables and bibliographies into documents. Running an installation of LaTeX on your own computer can make it difficult to work on a document collaboratively. The UVa Library has recently provided access for all UVa users to an on-line collaborative LaTeX editor, Overleaf. In this hands-on workhop, we’ll learn how to take full advantage of this powerful tool, so bring a laptop.

Workshop Materials


Information Design for Impact (Megan Copper) Thu 2/28 10:00 – 12:00 Brown 133
In this workshop, part one of a two-part series, we’ll learn about the value of graphic design for presenting information effectively and memorably. We’ll introduce key building blocks — balance, color, texture and more — and consider how they intersect with perception and cognition. Finally, we’ll talk about design workflows and introduce useful resources.


MS Word for Theses and Long Documents (Christine Slaughter) Wed 3/6 1:00 – 3:-00 Brown 133
If you plan on using Word for your next research paper, thesis, dissertation, or book manuscript, come to this session to learn tips and tricks that will save you time and headaches.

 

 


Information Design in Adobe Illustrator (Megan Copper) Thu 3/7 10:00 – 12:00 Brown 133
In this second workshop on information design, we’ll get more hands-on, learning the foundations of Adobe Illustrator – a vector drawing tool for graphic design and illustration. We will dig into Illustrator’s core tools and techniques, and work through a series of practical examples to explore how various features can be combined to convey information graphically. An installation of Adobe Illustrator is recommended, but not required. Trial plans are available at https://creativecloud.adobe.com/apps.



Colleagues across the university offer workshops in computational resources, programming, and data!
All Library Workshops || HSL Data Workshops || CADRE/SOMRC Workshops  || ARCS Workshops