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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.
This four-part, interactive workshop series is your complete introduction to programming Python for people with little or no previous programming experience. By the end of the series, you will be able to apply your knowledge of basic principles of programming and data manipulation to a real-world social science application.
Part 1 Topics:
Data are the foundations of the social and biological sciences. Familiarizing yourself with a programming language can help you better understand the roles that data play in your field. Learn to develop and train your data skills at the free D-Lab R workshops!
This four-part, interactive workshop series is your complete introduction to programming Python for people with little or no previous programming experience. By the end of the series, you will be able to apply your knowledge of basic principles of programming and data manipulation to a real-world social science application.
Part 1 Topics:
Data are the foundations of the social and biological sciences. Familiarizing yourself with a programming language can help you better understand the roles that data play in your field. Learn to develop and train your data skills at the free D-Lab R workshops!
This workshop covers how to organize and analyze qualitative data in Atlas.ti. The training will explore what CAQDAS (qualitative analysis) software is, and the benefits of using it to review and analyze your qualitative fieldnotes, text, video, or audio.
Wondering if you've provided enough information about how you collected and analyzed your qualitative data? Bring a draft of the data and methods section of a paper or article to get feedback! Attendees will exchange sections and provide each other with feedback. Please bring 2 copies of the sections you'd like others to read.
An intro to the basics that instructors often assume you know, but that you probably never had good instruction on! After this course, you should be able to more easily start learning to program (e.g., in our R or Python Fundamentals series), follow instructions and documentation online (e.g., StackExchange), and communicate better with your collaborators who are programming.
This three-part series will cover the following materials:
Part I: Introduction (Wednesday, January 25)
Wondering if the link between your claims and evidence is clear? Bring a draft of the findings section of a paper or article to get feedback! Attendees will exchange sections and provide each other with feedback. Please bring 2 copies of the sections you'd like others to read.
This three-part series will cover the following materials:
Part I: Introduction (Wednesday, January 25)
This workshop covers how to organize and analyze qualitative data in Dedoose. The training will outline the key decisions the researcher must make in the coding process, as well as teach attendees how to start a new Dedoose project, add codes and set up a code system, code data, add characteristics about data, run analysis tools such as queries, and explore data for further analysis.
This three-part series will cover the following materials:
Part I: Introduction (Wednesday, January 25)
This workshop covers how to organize and analyze qualitative data in MaxQDA. The training will outline the key decisions researchers must make about approaching coding and what data is most relevant, as well as review how to set up a database, and use folders, codes, document variables, and queries in MaxQDA.
Bring your interview questions to test them out and get feedback!
Attendees will get to try out their interview questions on other attendees and get feedback on their questions. This workshop is best suited for qualitative interviews that are semi-structured or structured. Please bring 2 copies of the questions you'd like to try out.
Diana Lara Rodgers will walk attendees through an example of how Atlas.TI was used for the research project described here:
Exploring how non‐Mexico City residents access abortion services in Mexico City: A qualitative study
This research presentation will walk attendees through an example of how MaxQDA was used for the research project described here:
The De-Racialization of Latino Space: Gentrification and Race in San Francisco, 1990-2014
This introductory workshop provides guidance and advice on how to prepare for qualitative data analysis whether you are using a QDA package like Atlas.TI, Dedoose, or MaxQDA, working with Word or Excel, or using scissors and highlighters.
This four-part, interactive workshop series is your complete introduction to programming Python for people with little or no previous programming experience. By the end of the series, you will be able to apply your knowledge of basic principles of programming and data manipulation to a real-world social science application.
Data are the foundations of the social and biological sciences. Familiarizing yourself with a programming language can help you better understand the roles that data play in your field. Learn to develop and train your data skills at the free D-Lab R workshops!
In this workshop we will cover two main supervised text analysis methods, the dictionary method, and supervised classification. We will use list comprehension to implement the dictionary method, using sentiment analysis as our example.
