Cologne, Germany

Introduction to Stata for Data Analysis

online course
when 28 July 2021 - 30 July 2021
language English
duration 1 week
fee EUR 160

This 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 who wish to refresh their skills. The course will not cover basic statistical methods and their underlying mathematics but how to apply these methods using Stata.
In the first part of the course, we will cover the program's interface and introduce its syntax structure and basic rules to write clean and reproducible Stata code. Subsequently, we will provide you with skills in hands-on data management, common data analyses, and the visualization of results. Depending on the participants' prior knowledge, we will be able to give further insight into the automatization of data wrangling and analysis procedures, as well as the export of publication-ready results. Also, 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.

Course leader

Nils Jungmann and Anne-Kathrin Stroppe are doctoral researchers working as a data curators for the German Longitudinal Election Study (GLES) at GESIS, Germany.

Target group

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

Prerequisites:
- Familiarity with quantitative data
- Basic knowledge of uni- and bivariate statistics (e.g. descriptive statistics, basics of regression analysis)
- Knowledge of other syntax-based software is helpful but not required

Course aim

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

Fee info

EUR 160: Student/PhD student rate.
EUR 240: Academic/non-profit rate.
The rates include the tuition fee and the course materials.