Programming with R

An introduction to R for non-programmers using gapminder data

The goal of this lesson is to teach novice programmers to write modular code and best practices for using R for data analysis. R is commonly used in many scientific disciplines for statistical analysis and its array of third-party packages. We find that many scientists who come to Software Carpentry workshops use R and want to learn more. The emphasis of these materials is to give attendees a strong foundation in the fundamentals of R, and to teach best practices for scientific computing: breaking down analyses into modular units, task automation, and encapsulation.

Spanish version available here

Github repository available here

Learn about the use of programming for data analysis, data management, and statistical analysis techniques.

The workshop Applied Data Visualization introduces students to the theory and methods underlying data visualization. Data analysts face an ever-increasing amount of data (→ big data) and rather revolutionary technological developments allow researchers to visually engage with data in unprecedented ways. Hence, data visualization is one of the most exciting fields in data science right now. In this workshop students acquire the skills to visualize data in R both for exploratory purposes as well as for the purpose of explanation/presentation. We'll rely on R, the most-popular statistical programming environment when it comes to visualization and we'll make use of popular R packages such as ggplot2 and plotly. Besides creating static graphs we'll also have a look at interactive graphs and discuss how interactive visualization may revolutionize how we present data & findings.

Please note, this is an example of a possible workshop. Some workshops are offered regularly. An updated workshop list is to be found under the link provided under the Access point.

Practical tutorials to manage and handle research data for particular software packages: SPSS, R, ArcGIS and N-Vivo. Tutorials contain many practical exercises.

This workshop uses a tabular interview dataset from the SAFI Teaching Database and teaches data cleaning, management, analysis and visualization. There are no pre-requisites, and the materials assume no prior knowledge about the tools. We use a single dataset throughout the workshop to model the data management and analysis workflow that a researcher would use.

Have a Binder-Ready repository? With GESIS Notebooks, turn this repository into a persistent Jupyter environment, allowing you to continue your analysis from anywhere at any time.

This service is intended for use by social scientists. You can build and launch all binder-ready projects without logging in. If you want to have more persistent projects, you need to log in.

At GESIS we offer a wide range of events, especially training courses on empirical social research methods. Our theory founded and hands-on courses develop participants’ methods skills and are aimed at both early career and senior researchers from Germany, Europe, and the whole world.

Library Carpentry workshops teach people working in library- and information-related roles how to:

• Cut through the jargon terms and phrases of software development and data science and apply concepts from these fields in library tasks;
• Identify and use best practices in data structures;
• Learn how to programmatically transform and map data from one form to another;
• Work effectively with researchers, IT, and systems colleagues;
• Automate repetitive, error prone tasks.

About 200 online courses dedicated to various disciplines including humanities and social sciences.

Teaching basic lab skills for research computing. Lessons and workshops in three core topics: the Unix shell, version control with Git, and a programming language (Python or R).