We offer, coordinate, and highlight workshops and training on data analysis and statistics, computation and software, as well as on Library resources and methods. Anyone in the UVA community may attend. It’s free! Feel free to email us recommendations for workshops you’d like to see: email@example.com.
RDS Workshops: Spring 2018 Click the date to register! (Registration is not required, but we usually send out an email ahead of time with links to resources you’ll need for the workshop, and we don’t want you to miss out!)
|Workshop Topic (Instructor)||Day||Time||Location|
|Introduction to Unix (Ricky Patterson)||Tue, 1/23||10:30 – 12:00||Brown 133|
|This workshop will introduce new users to the command line interface and Unix shell commands. This would be useful both for users interested in using Unix on a local machine (including Linux and Mac OS X), as well as users who want to make use of remote resources such as the Rivanna cluster. Users will learn how to create and navigate directories, and to create, copy, move, and search files. We will also cover setting and changing file permissions, and creating symbolic links. Redirection of output and job control, with a brief discussion of shell scripts. Users will need to bring their own laptop in order to fully participate in the workshop.
|Introduction to Stata (Clay Ford)||Thur, 1/25||10:00 – 12:00||Brown 133|
|This workshop will get you up and running with Stata, the powerful statistical software program that provides just about everything you need for analysis and graphics. We’ll cover getting your data into Stata, cleaning and preparing your data, running some simple statistical analyses, and generating a few graphs. We’ll also talk about how to get the most out of Stata’s excellent online manuals so you can help yourself go further with Stata. The workshop is designed for the beginner and assumes no prior knowledge of Stata.
|Introduction to R (Clay Ford)||Wed, 1/31||10:00 – 12:00||Brown 133|
|Designed for the absolute beginner, 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. Since its introduction in 2000, R has rapidly increased in popularity thanks to its power, price (free!), and supportive community. RStudio is a free integrated development environment (IDE) that makes using and learning R much easier. In this workshop we’ll get you started using R with RStudio, show you how to import data, do some basic data manipulation, create a few graphics, perform some basic statistical analyses, and point you in the direction to learn more and go further with R!
|Working with Data in Excel (Nancy Kechner)||Thur, 2/1||10:00 – 11:00||Brown 133|
|This workshop is for those new to Excel as a data tool. We will cover the interface, writing formulas, creating charts, and working with pivot tables.
|Exploratory Factor Analysis (Clay Ford)||Tues, 2/6||10:00 – 12:00||Brown 133|
|Intelligence. Compassion. Depression. Determination. Anxiety. Leadership. These are examples of qualities, or factors, that are difficult to measure directly. But we may be able to infer their existence from quantities that we can measure such as survey questions or test scores. Exploratory Factor Analysis, or EFA, is the statistical method of exploring data for the possible existence of such factors. In this workshop we introduce the basics of EFA and demonstrate how to perform an EFA using the R statistical programming environment. Prerequisites: basic understanding of correlation and covariance. Might also be helpful to know how to open a R script in RStudio and submit R code, though we’ll demonstrate that in the workshop.
|Help! I need to use the Census (Jenn Huck)||Wed, 2/7||2:00 – 3:00||Brown 133|
|Learn the basics of Census data, and how and why you want to use it. We will review useful sites for pulling Census data, including Social Explorer.
|LaTeX & ShareLaTeX (Ricky Patterson)||Thur, 2/8||10:30 – 12:00||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, ShareLaTeX. Come learn how to take full advantage of this powerful tool. Participants will need to bring their own laptop for this workshop.
|Linear Mixed Effects Modeling in R (Clay Ford)||Mon, 2/12||10:00 – 12:00||Brown 133|
|Mixed-effect models, multilevel models, hierarchical linear models – all refer to a class of statistical models used to analyze correlated data. Such data include repeated measurements, longitudinal measurements and clustered observations. In this workshop we introduce the basics of mixed-effect modeling with an emphasis on implementation and interpretation. Examples will be given in R using the lme4 package. Previous experience with R and linear regression will be helpful but not required.
|Introduction to Qualtrics (Nancy Kechner)||Tues, 2/13||10:00 – 11:00||Brown 133|
|Qualtrics is an online survey software package which makes sophisticated research simple and empowers users to capture a wide variety of information easily. In this workshop, we’ll cover some basics of creating, implementing, and analyzing a survey in Qualtrics.
|Confirmatory Factor Analysis (Clay Ford)||Tue, 2/20||10:00 – 12:00||Brown 133|
|When we perform an Exploratory Factor Analysis (EFA), we’re not sure how many factors exist (if they exist at all) or what the factors represent. But when we hypothesize the existence of a certain number factors and how they manifest themselves through observable variables, we turn to Confirmatory Factor Analysis, or CFA, to test our hypothesis. In this workshop we introduce the basics of performing a CFA using the R statistical programming environment. Using the laavan and semPlot packages, we cover how to specify CFA models, how to interpret the output, how to evaluate fit, and how to create path diagrams summarizing our results. Prerequisites: Basic understanding of Exploratory Factor Analysis. Might also be helpful to know how to open a R script in RStudio and submit R code, though we’ll demonstrate that in the workshop.
|Funding Discovery Tools (Ricky Patterson)||Wed, 2/21||10:00 – 11:00||Brown 133|
|Funding discovery databases help researchers identify opportunities from public and private funders. UVa now has access to two discovery tools licensed by the Vice Provost of Research, Pivot and GrantForward. These tools allow faculty, students and staff to search for funding and set up email search alerts based on a researcher’s area of interest. After the workshop, the 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. All students, faculty and staff at the University have access and the ability to create personal accounts. Please bring a laptop for use for this hands-on workshop.
|Literate Data Science in Stata (Alex Jakubow)||Tue, 2/27||2:00 – 3:30||Brown 133|
|Literate statistical programming can improve the efficiency and reproducibility of our research. This workshop explores tools for weaving code, results, and interpretation into integrated documents in Stata. We will consider default solutions bundled with Stata 15, as well as community-created alternatives. We will also illustrate multiple output formats (e.g., .html, .tex, .pdf). Prior knowledge of markdown is helpful but not required.
|Data Sharing & Archiving for Engineering (Bill Corey/Erich Purpur)||Tue, 3/13||10:00 – 11:30||Brown 133|
|This workshop covers the best practices for data sharing and archiving of research data for the engineering sciences. We will explore why you should share your data; how to share it safely and efficiently; the difference between storage and archiving; and how to identify and locate a repository. There will be time for you to ask questions specific to your discipline, too. Please bring your laptop for some hands-on work. We’ll be using Google Slides so you’ll need a Google account.
|Research Management and Reproducible Practices with the Open Science Framework (Ricky Patterson/Sherry Lake)||Thur, 3/15||2:00 – 4:30||Brown 133|
|Workshop description coming soon!
|Data Visualization with Tableau (Nancy Kechner)||Thur, 3/22||10:00 – 11:30||Brown 133|
|This is an introduction to the increasingly popular Tableau platform for creating dynamic data visualizations on the web. We’ll go over the interface, adding data sources, and building multiple types of interactive visualizations on the web.
|Introduction to Python (Pete Alonzi)||Tue, 3/27||10:00 – 12:00||Brown 133|
|This workshop covers the fundamentals of python beginning with setting it up on your system. No prior experience is required. Just bring your laptop. We will start with installation and then move to interpreted coding focusing on the built-in data types. This will be a hands on experience with exercises throughout and plenty of time to get your hands dirty.
|Data Sharing & Archiving for the Physical Sciences (Bill Corey/Jeremy Garritano)||Thur, 3/29||10:00 – 11:30||Brown 133|
|This workshop covers the best practices for data sharing and archiving of research data for the physical sciences. We will explore why you should share your data; how to share it safely and efficiently; the difference between storage and archiving; and how to identify and locate a repository. There will be time for you to ask questions specific to your discipline, too. Please bring your laptop for some hands-on work. We’ll be using Google Slides so you’ll need a Google account.
|Introduction to Dedoose (Nancy Kechner?)||Thur, 4/5||10:00 – 11:30||Brown 133|
|New to Qualitative Research? Imagine being able to blend your video, audio, and text data with your spreadsheet information in an on-line tool to get the most out of all of your information! Dedoose is an easy to learn, feature rich, and affordable web app that can help you visualize a variety of information from your work that you can share with the research community. Come and see Dedoose in action to see if you want to add qualitative analysis to your research toolbox.
|Text Analysis in R: Quanteda (Michele Claibourn)||Tue, 4/10||10:00 – 12:00||Brown 133|
|This workshop covers how to perform common text analysis and natural language processing tasks using R, relying heavily on the well-rounded quanteda package (https://github.com/kbenoit/quanteda). When used properly, R is a fast and powerful tool for managing even very large text analysis tasks. We will go over formatting and inputting source texts, structuring metadata, and prepare text for analysis. We’ll show how to: get summary statistics from text, search for and analyse keywords and phrases, analyse text for lexical diversity and readability, apply dictionaries, and more. Structured objects from quanteda can be readily passed into other text analytic packages for additional analyses like topic modelling, regression models, and other forms of machine learning – though this workshop will not cover these advanced techniques. While it will be valuable to have some prior experience in R, expertise in R is not required, and even those with no previous knowledge of R are welcome.
|Introduction to Git/GitHub (Pete Alonzi)||Thur, 4/12||10:00 – 12:00||Brown 133|
|Git is a program in the class of version control software. Proper use will help you to manage your development. Until recently the software has been a burden to operate but the development of Github.com has changed that. In this workshop we will explore the use of git through the github framework. We will work with the web interface and the desktop client. Please bring your laptops. The use of github requires a user account so please set one up prior to arrival at github.com.
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