Data Inquiry Lab (DIL)
The Data Inquiry Lab (DIL) provides support for student-led quantitative data management, visualization, and analysis. From workshops, and in-classroom demonstrations, to one-on-one consultation, the DIL’s purpose is to develop practical data skills of GVSU students, faculty, and staff.
The DIL operates during the fall and winter semesters. A list of workshops --- freely available to everyone in the GVSU community --- are listed below.
The DIL is managed by Faculty Fellow Whitt Kilburn, Associate Professor of Political Science, Faculty Associate Gerald Shoultz, Associate Professor of Statistics, with Graduate Assistant Joel Smith, M.S. Candidate in Biostatistics.
Drop-in Hours and Appointments
Drop-in consultations begin September 6, and continue throughout the Winter semester. Stop by LIB 135, in the Knowledge Market of the Mary I. Pew library on the Allendale campus. Speak with our Graduate Assistant, Joel Smith, during the following hours:
Tuesday, 10-2:30 p.m.
Thursday, 10-2:30 p.m.
In addition, consultation hours are available with faculty associates by request. Please use the form or email below to inquire about availability.
The DIL provides consultations on use of common statistical and data analysis software applications, from Excel, R, SAS, SPSS, and Stata to online, web-based applications such as Tableau and Plot.ly.
Students should please fill out a brief questionnaire to schedule an appointment. Faculty and staff should contact Whitt Kilburn, email@example.com.
Prior Workshops on Data Analysis
DIL staff have held workshops on the following subjects, among others. Materials from these workshops are available upon request. DIL faculty are happy to host in-class workshops for faculty and private consultations with members of the GVSU community on any of the following:
Introduction to R:
A workshop intended for those totally new to the R analysis system. Learn to use R for your own projects in the sciences and digital humanities.
Learn to use the IBM SPSS point-and-click interface for data import, descriptive statistics, and fundamental visualizations.
Learn to code basic SAS procedures for data import, descriptive statistics, and fundamental visualizations.
Easy Data Visualization with Plot.ly
Learn Plot.ly’s easy `plug and play’ system for data visualization; workshop will replicate graphics from The New York Times’ The Upshot”, from data collection to visualization.
Social Media Data Collection, Visualization, and Analysis
Learn easy R tools for sampling Twitter streams. An overview of other social media tools.
Text as Data: Sentiment Analysis
An introduction to lexicon (dictionary) based analyses of text affect and tone; applications will include social media posts, open-end survey responses, and literary texts.
SPSS: Computing and Recoding Variables, Chart Editor
Learn to use the SPSS Chart Editor for data visualization and Transform capabilities for data management.
SPSS: Simple and Multiple Linear Regression
Learn tools for estimating, interpreting, and diagnosing problems with simple and multiple linear regression
Text as Data: Stylometry
An introduction to the analysis of countable linguistic features of text documents, such as word and letter n-grams, to reveal differences in authorship and style.