Data Wrangling in Stata, Part 1

"Data Wrangling" is the process of preparing data for analysis, which includes importing, cleaning, recoding, restructuring, combining, and anything else data needs before it can be analyzed. Data wrangling is a critical skill for research.

In this class you'll learn how to wrangle data using Stata. We'll cover some of the key concepts and workflows of data science as well as the structure and logic of Stata. We'll emphasize real-world issues like handling missing data and checking for errors, as well as best practices for research computing and reproducibility. Our goal is give you a strong foundation you can build on to become an expert data wrangler.

In part one, we'll focus on reading data into Stata, and then the first steps in understanding its structure and cleaning it up for use. We'll cover sections one through three of the online curriculum.

Students should take SSCC's Introduction to Stata or have equivalent experience before taking this class. You should be comfortable writing do files and understand all the component parts of a command like 'sum x if y>5, detail'. Graduate students may choose to take this class at the start of their graduate student career or wait until they are ready to start doing research.

Instructor: Dimond
Room: 3218 Sewell Social Sciences Building
Dates: 2/2, 2/7, 2/9
Time: 2:00 - 4:00

Each session of this class builds on the material taught in the previous sessions. If you cannot attend all of the class's sessions but still want to take the class, you must contact the Help Desk, find out what will be covered in the session(s) you will miss, and learn that material on your own before the next session. In most cases the material can be found in the SSCC Knowledge Base.


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