Introduction to Stata for Data Management and Analysis

About

The course will give a thorough introduction to the software Stata. It is tailored to the needs of academics and other research practitioners who are new to Stata or wish to refresh their skills. The course will not cover basic statistical methods and their underlying mathematics but will focus on their practical application using ALLBUS data in Stata.

In the first part of the course, we will cover the program's interface and introduce its syntax structure and basic rules for writing clean and reproducible Stata code. Subsequently, we aim at enhancing the participants’ skills in hands-on data management, common data analyses, and the visualization of results. Depending on the participants' prior knowledge, we might provide further insight into the automatization of data wrangling and analysis procedures and the export of publication-ready results. Additionally, we will review available help and support features (online and offline) to equip participants with the necessary knowledge to further develop their skills and solve occurring problems. This course will be interactive and case-based in nature.

Course leader

Mazlum Karatas is a postdoctoral researcher with the CEWS team and Lynn-Malou Lutz works at the Deutschland-Monitor project at the department “Data and Research on Society” at GESIS Leibniz Institute for the Social Sciences.

Target group

You will find the course useful if:
- you are new to statistical computing (with Stata),
- you are familiar with other statistical software but want to get to know Stata,
- you have already worked with Stata before but want to refresh basic knowledge.

Prerequisites:
- Familiarity with quantitative (survey) data
- Basic knowledge of uni- and bivariate statistics (i.e., descriptive statistics, basics of regression analysis)

Course aim

By the end of the course, you will:
- be familiar with Stata's interface and facilities,
- understand how to integrate Stata into your research process to create reproducible and publication-ready results,
- know how to solve common data management problems in Stata and how to document all modifications of the data,
- be able to perform typical descriptive and inferential statistical procedures and use graphs to communicate your results effectively,
- know how to proceed from here and get additional support if needed.

Fee info