We offer, coordinate, and highlight workshops and training on data analysis and statistics, computation and programming, software and other useful stuff. Anyone in the UVA community may attend. It’s free! Feel free to email us recommendations for workshops you’d like to see: firstname.lastname@example.org.
StatLab Workshops: Fall 2016 Click the date to register!
|Workshop Topic (Instructor)||Day||Time||Location|
|Introduction to R (Clay Ford)|| Thursday, 9/1
|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!
|Introduction to Stata (Michele Claibourn)||Tuesday, 9/6||10:00-11:30||Brown 133|
|Stata is a useful and powerful statistical programming package widely used across a variety of disciplines. This workshop is aimed at users new to Stata and will introduce the main windows in the Stata environment, the basic Stata command syntax, and the use of do-files to set up and save commands and procedures. We will focus primarily on data management and manipulation — Importing data, defining variables and attributes, generating and recoding variables, sorting and checking data, and some basic summary and descriptive analyses. If time permits, we’ll talk about generating graphics in Stata. The workshop is designed to help you become comfortable working in Stata so that you can begin to learn new applications on your own.
|Linear Modeling with R (Clay Ford)||Tuesday, 9/13||10:00-11:30||Brown 133|
|This workshop will cover how to carry out multiple regression, ANOVA, model selection, model validation and diagnostics using the R statistical computing environment. Special emphasis will be placed on extracting model information within R for the purpose of reporting or further analysis. This workshop is ideal for those familiar with linear modeling in other programs (such as Stata or SPSS) but who want to learn how to do it in R. This can also serve as a refresher for forgotten statistics! Previous experience with R will be helpful but not required.
|Building Shiny Web Apps in R (V.P. Nagraj)||Wednesday, 9/14||10:00-11:30||Brown 133|
|Shiny is a framework for developing interactive, web-based tools with R. This workshop will cover how to create a basic user interface, add reactive widgets and publish a Shiny app. No web development experience is required. Some familiarity with R will be helpful.
|Introduction to LaTeX (Ricky Patterson)||Wednesday, 9/21||10:00-11:30||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. While new users may appreciate the transparency and control over document creation with LaTeX, they can also struggle with the steeper learning curve when compared to a WYSIWYG word processing program such as Microsoft Word.
This workshop is aimed at users new to LaTeX. It will introduce the structure of LaTeX documents, and cover topics including editing and compiling documents, and how to find and use packages. There will be an overview of basic formatting, document layout, and the creation of figures, tables, and equations. Finally, there will be a brief overview of Overleaf and ShareLaTeX, collaborative platforms available for editing and compiling LaTeX documents.
Participants will need to have a working installation of LaTeX; an installation guide will be available before the workshop.
|Visualization in R with ggplot2 (Clay Ford)||Thursday, 9/22||10:00-11:30||Brown 133|
|The ggplot2 package has revolutionized data visualization with R. With its consistent syntax and layered approach to making graphics, ggplot2 allows you to rapidly visualize your data in ways that previously required tedious programming. In this workshop we introduce the logic behind ggplot2, how to use ggplot2 to explore your data, and how to customize and polish ggplot2 graphs. No prior experience with ggplot2 is assumed, though some experience with R would be helpful.
|Introduction to Python, Part 1 (Pete Alonzi)||Tuesday, 9/27||3:30-5:00||Brown 133|
|This workshop covers the fundaments 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.
|Exploring Data with Excel (Nancy Kechner)||Wednesday, 9/28||2:00-3:30||Ruffner 302 (LDC@C)|
|Excel can be found on nearly every computer, and with very little training you can be organizing and visualizing your data in no time. Join us for a soup-to-nuts intro to the power of Excel from data entry, writing effective formulas to calculate new values, conditional formatting to show trends, chart/graph creation to show results, and pivot tables to show relationships in your data. Please bring a computer with Excel loaded on it or a computer that can connect to The Hive.
|Creating Tables and Figures with LaTeX (Ricky Patterson)||Wednesday, 10/5||10:00-11:30||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.
This workshop will introduce LaTeX users to the creation and formatting of tables and figures within a LaTeX document. Participants will learn how to create and format multi-page tables. They will also learn how to create simple figures within LaTeX itself, as well as how to format imported figures. Participants will need to have a working installation of LaTeX on a laptop.
|Introduction to Python, Part 2 (Pete Alonzi)||Tuesday, 10/11||3:30-5:00||Brown 133|
|This is the second installment in a series you should take Part I before this Part or have some experience with python already. We assume you already have python installed on your system and will be working within the Anaconda distribution. We will cover advance interpreter features in ipython and make use of the spyder integrated development environment. We will discuss programming features such as functions and will work with python packages. Bring your laptop. This will be a hands on experience with exercises throughout and plenty of time to get your hands dirty.
|Visualizing Model Effects (Clay Ford)||Thursday, 10/13||10:00-11:30||Brown 133|
|Linear modeling output can be difficult to interpret, especially when your model has interactions. What do the coefficients on the interactions mean exactly? In the presence of multiple predictors, interactions can defy intuition. On top of that, you may have multiple models to compare. Traditionally these are summarized in a table crammed with rows of coefficients, standard errors and test statistics. But our brains often struggle to process so many numbers and detect patterns and differences. In this workshop we show you how to address these issues in R using effect displays and coefficient plots. These methods allows us to visualize linear model output and help us interpret and communicate their meaning. Prerequisites: some experience using R and basic knowledge of multiple and logistic regression would be helpful, but not required.
|Visualization in Python (Pete Alonzi)||Tuesday, 10/18||3:30-5:00||Brown 133|
|We will explore how to take your data from bits in memory to beautiful images on the screen. The most popular package is matplotlib and we will work extensively with that. We will also use bokeh for some interactive work. Bring your laptop. This will be a hands on experience with exercises throughout and plenty of time to get your hands dirty.
|Creating and Managing Bibliographies in LaTeX (Ricky Patterson)||Wednesday, 10/19||10:00-11:30||Brown 133|
|Reference management and bibliography creation can be a real challenge when writing an research paper, journal article, or dissertation. This workshop will introduce the bibliographic options available when creating a document with LaTeX. In particular, it will focus on BibTeX, a bibliographic database tool that is used with LaTeX to manage references and create a bibliography for a LaTeX document. Topics covered will include creation and management of BibTeX references files, creation of bibliographies with using both BibTeX files as well as internal citations, changing bibliographic style using and importing references from Refworks, EndNote, Zotero or Mendeley into BibTeX.
|Natural Language Processing with Python (Jon Ashley)||Tuesday, 10/25||10:00-11:30||Brown 133|
|This workshop is an introduction to Natural Language Processing and some of the basic processes that can be applied to a corpus of texts. We will cover preparation of texts, tokenization, part of speech tagging, and topic modeling. Although there are a variety of NLP packages available in Python we will be using “spaCy”. Prior experience with Python is helpful.
|Survival Analysis, using Stata (Alex Jakubow)||Tuesday, 11/8||10:00-11:30||Brown 133|
|Social scientific and biomedical researchers are frequently interested in understanding the time to the occurrence of some event—such as the death of a participant in a clinical trial or the end of a governing coalition. This workshop introduces key methodological concepts in survival analysis and contrasts fully-, semi-, and non-parametrized modeling frameworks. Examples from Stata illustrate how to prepare a dataset for survival analysis, interpret regression results, and conduct important diagnostic tests. This workshop assumes participants are comfortable with multivariate regression and familiar with the analysis of limited/categorical dependent variables. Prior experience with Stata is helpful but not required.
|Manipulating List Objects in R (V.P. Nagraj)||Wednesday, 11/9||10:00-11:30||Brown 133|
|Formatting data as a list can be necessary in some cases. However, retrieving this kind of non-tabular information for analysis can be challenging. This workshop will introduce students to the motivations and techniques for storing and parsing list objects in R. Some familiarity with R will be helpful.|