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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
  • Cross-tabulations

Part 2: Data Analysis in Stata

  • Correlation
  • T-tests
  • 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

Software Requirements: Installation Instructions (note: UC Berkeley students will receive an email with an instructional license for the workshop)

Date & Time

Date:
October 17, 2023
Time:
2:00pm - 5:00pm

Location

Online via Zoom

Website

Website:

Organizer

D-Lab