This workshop will cover how to determine the geographic coordinates for address data. This is useful for creating maps, linking to other geospatial data, or finding distances between points. We will use two open source geocoders: Photon and The Data Science Toolkit. Participants will learn how to make API calls, how to parse the data, and how to map the results.
Sign up for our weekly newsletter!
This is an archive of our past training offerings. We are looking to include workshops on topics not yet covered here. Is there something not currently on the list? Send us a proposal.
March 28, 2016
Author:
Juan Shishido
Workshop: Python for Everything: Part 3
March 18, 2016
Author:
Dillon Niederhut
This four part, interactive workshop series is your complete introduction to the capabilities of the Python language. By the end of the series, you will be able to apply your knowledge of basic principles of programming and data manipulation to collect data, process unstructured data, analyze tabular data, and automate the entire process.
Workshop: Geocoding without Programming
March 18, 2016
Author:
Patty Frontiera
This workshop will introduce geocoding - the process of determining the geographic location of a place name, zipcode or address. The first part of this workshop will be an introduction to the process of geocoding and strategies for achieving good results.
March 17, 2016
Join the Qualitative Methods Group (QMG) for a conversation with advanced graduate student Summer Starling about visually presenting qualitative data.
Workshop: R for Data Science: Day 3
March 16, 2016
Author:
Evan Muzzall
The R for Data Science workshop series is a four part course, designed to take novices in the R language for statistical computing and produce programmers who are competent in finding, displaying, analyzing, and publishing data in R.
Day 3 (analyzing data)
March 16, 2016
Author:
Susan Powell
** CANCELLED *** ** CANCELLED *** To be Rescheduled ***
Workshop: Citation Management in Zotero
March 15, 2016
Author:
David Eifler
Citation management software can help organize research results and make writing papers easier by quickly creating properly formatted bibliographies and footnotes.
Workshop: Python for Everything: Part 2
March 11, 2016
Author:
Juan Shishido
This four part, interactive workshop series is your complete introduction to the capabilities of the Python language. By the end of the series, you will be able to apply your knowledge of basic principles of programming and data manipulation to collect data, process unstructured data, analyze tabular data, and automate the entire process.
March 11, 2016
Author:
Zawadi Rucks-Ahidiana
Coding is done, now what? You’ve finished coding your qualitative data and now it’s time to start the “analysis” process. Where do you start? Through this interactive workshop session, qualitative researchers will learn several approaches to transition from coding to analysis. Researchers in all phases of the qualitative research process are welcome to attend.
Workshop: Introduction to SAS
March 10, 2016
Author:
Juan Shishido
This workshop will introduce students to the SAS system. Participants will gain an understanding of the SAS environment as well as the functionality it provides, which includes data management and analysis. Students will learn the basics of the SAS programming language through examples, loading data sets and using built-in procedures.
Workshop: R for Data Science: Day 2
March 9, 2016
Author:
Shinhye Choi
The R for Data Science workshop series is a four part course, designed to take novices in the R language for statistical computing and produce programmers who are competent in finding, displaying, analyzing, and publishing data in R.
Day 2 (clean and tidy data)
Workshop: Stata Programming
March 4, 2016
Author:
Chris Kennedy
This is the third workshop in a 3-part Stata series offered at the D-Lab that includes: 1) Intro to Stata, 2) Data Analysis in Stata and 3) Stata Programming.
Workshop: Python for Everything: Part 1
March 4, 2016
Author:
Kunal Marwaha
This four part, interactive workshop series is your complete introduction to the capabilities of the Python language. By the end of the series, you will be able to apply your knowledge of basic principles of programming and data manipulation to collect data, process unstructured data, analyze tabular data, and automate the entire process.
Workshop: Qualitative Data Analysis with Atlas.TI
March 4, 2016
Author:
Zawadi Rucks-Ahidiana
This workshop covers how to organize and analyze qualitative data in Atlas.TI. Both researchers new to qualitative methods and experienced qualitative researchers are encouraged to attend.
Workshop: Geospatial Data Formats and Sources
March 3, 2016
Author:
Patty Frontiera, Susan Powell
This workshop will provide an introduction to digital geographic data - or geospatial data - and prepare you to work with these data in any software tool, whether it is desktop GIS like ArcGIS or QGIS or a programming language like R or Python.
Workshop: Brown Bag Series: How We Did It
March 3, 2016 to March 31, 2016
New brown bag series, "How We Did It", a bi-weekly, hour-long presentation on specific topics from quantitative data cleaning to best practices for entering the field for participant observation.
Workshop: Citation Management in Zotero
March 3, 2016
Author:
David Eifler
Citation management software can help organize research results and make writing papers easier by quickly creating properly formatted bibliographies and footnotes.
Workshop: R for Data Science: Day 1
March 2, 2016
Author:
Evan Muzzall
The R for Data Science workshop series is a four part course, designed to take novices in the R language for statistical computing and produce programmers who are competent in finding, displaying, analyzing, and publishing data in R.
Day 1 (basics of R)
March 2, 2016
Author:
Colleen Kohashi
This workshop provides a discussion of federal regulations overseeing human subjects research, levels of review and application submission guidance.
Workshop: Finding Health Statistics
March 1, 2016
Author:
Michael Sholinbeck
Participants in this workshop will learn about some of the issues surrounding the collection of health statistics, and will also learn about authoritative sources of health statistics and data. We will look at tools that let you create custom tables of vital statistics (birth, death, etc.), disease statistics, health behavior statistics, and more.
