In this workshop, you'll get a brief introduction on how to manage simple or complex websites using nothing more than a text editor and Git. Using the social and through-the-web features of GitHub, this enables the possibility of collaboration with folks from anywhere on the web, while maintaining clear control of your site.
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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.
Survey research is a fundamental form of data collection for social scientists, health professionals, businesses, and nearly any form of organization with more than a few members. This course will introduce the concepts, principles, and terminology of survey research; provide an overview of methods used to design and conduct surveys; and help you understand some major decisions you will need t
This workshop will be a dive into programming in Python. We will cover types, lists, loops, dictionaries, conditionals, and functions. By the end, you will have some practice with Python and other resources to further your learning.
This workshop will introduce methods and libraries for mapping spatial data in R.
Join the Qualitative Methods Group (QMG) for a conversation with Dr. Sandra Smith about writing up the findings of qualitative research. Dr. Smith will share her experiences and provide advice on how to approach the writing phase of the qualitative research process.
Linear modeling is the one of the most flexible methods available in inferential statistics, but this flexibility comes at a learning cost. This intermediate workshop in R provides an introduction in and best practices for linear modeling. These include:
Qualtrics is a powerful online tool available to Berkeley community members that can be used for a range of data collection activities including surveys, data entry, training, quality control, market research, event feedback. Following the general overview, this class will focus on questionnaire design using Qualtrics. This class will cover some best practices for designing questionnaires and
"pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with 'relational' or 'labeled' data both easy and intuitive." It enables "doing practical, real world data analysis in Python."
In this workshop, we'll work with example data and go through the various steps you might need to prepare data for analysis.
This session is the third of a three part series on regression discontinuity designs. We will discuss common problems that arise in applied RD and how they can be overcome. Having attended the previous sessions is not necessary, but some prior knowledge of RD would be very helpful.
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 4 (functions and packages)
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.
Join the Qualitative Methods Group (QMG) for a conversation with Dr. Cristina Mora about triangulating data across archival sources and interviews. Dr. Mora will share her experience implementing a qualitative mixed-methods research project.
This class will cover the the basics of simulations in R. We will begin by going through simple examples. We will then investigate how simulations can be used to solve more difficult problems in probability and statistics. A basic knowledge of R would be helpful.
The microblogging platform Twitter has become a popular tool both for the analysis of social data (relationship networks, information transmission, linguistic changes) and creating conversations around social issues.
This session is the second of a three part series on regression discontinuity designs. We will discuss smoothers, bandwidth selection, confidence intervals, and covariate adjustment. Sample code will be provided in R.
Check out the remaining workshops in this series:
This workshop will introduce two different web platforms for exploring and mapping US demographic data - SimplyMap and Policy Map. While there is some overlap between the different applications, each has its own strengths and unique features. For each platform I will provide a short demo, followed by some time to explore the data and visualization tools that each offers.
While a doctoral degree from Cal is most helpful in securing a tenure-track position, the truth is that not everyone wants to go that route, and there aren’t enough positions for everyone who completes a PhD. Non-academic careers offer a great deal of flexibility in terms of topic area, preferred geographic location, and compatibility with spousal careers.
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)
This introductory workshop will introduce attendees to the reason for using a qualitative data analysis package for the coding and analysis process. We will begin by discussing the distinction between coding and analysis, the benefits of using a QDA package, and then view a brief demonstration of a specific program.
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.