Please note: Everyone is placed on the waitlist at first. It may take up to 24 hours to confirm your UCB affiliation and then you will receive a confirmation email and calendar invite. You will need to finish your registration by filling out this form: https://dlab.berkeley.edu/affiliations
Location: Remote via Zoom. Link will be sent on the morning of the event.
Date & Time: This workshop is a 3-part series running from 9am-12pm each day:
- Part 1: Wednesday, October 20
- Part 2: Friday, October 22
- Part 3: Monday, October 25
Start Time: D-Lab workshops start 10 minutes after the scheduled start time (“Berkeley Time”). We will admit all participants from the waiting room at that time.
This workshop is a three-part introductory series that will teach you Stata from scratch with clear introductions, concise examples, and support documents. You will learn how to download and install the Stata software, understand data and basic manipulations, import and subset data, explore and visualize data, and understand the basics of automation in the form of loops and functions. After completion of this workshop you will have a foundational understanding to create, organize, and utilize workflows for your personal research.
Each of the parts is divided into a lecture-style coding walkthrough interrupted by challenge problems, discussions of the solutions, and breaks. Instructors and TAs are dedicated to engaging you in the classroom and answering questions in plain language.
Part 1: Introduction
- Loading datasets into Stata (no previous knowledge expected)
- Examining a dataset and finding variables of interest
- Summarizing and tabulating variables
- Stata specific tools and resources (do files, logs, help files, etc.)
- Coding and cleaning data (making new variables from old variables; labeling variables and values, etc.)
- Using logical operators in Stata
Part 2: Data Analysis in Stata
- Ordinary Least Squares (OLS) and logistic regression (basic syntax, using interaction terms, interpreting output)
- Visualization (histograms, bar graphs, scatter plots)
- Regression postestimation (getting predicted values, basic graphs)
- Merging and appending datasets
Part 3: Stata Programming
- Local and global variables (macros)
- Looping (foreach, forvalues)
- Reshaping data between wide and long formats
- Recalling and using command output
- Generating nicely formatted journal-style tables
Workshop Materials: https://github.com/dlab-berkeley/stata-fundamentals
Questions? Email: firstname.lastname@example.org