Statistical software

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

The aim of the course is to introduce digital humanities and to describe various aspects of digital content processing. The practical aims consist of introducing current data sources, annotation, pre-processing methods, software tools for data analysis and visualisation, and evaluation methods.

Currently, we identified that students are somewhat aware of digital humanities but it is difficult for them to dive in and, mainly, to anticipate what they should learn for their future research. A more detailed goal of this course is to present some current projects, show the datasets and technologies behind, and encourage students to explore the datasets and use the technologies on data they already know. A high level goal is to set the knowledge of the technologies and available datasets into the research iteration loop (create hypotheses -> design instruments -> collect data -> analyze and evaluate).

Taken from: Teaching with CLARIN: https://www.clarin.eu/content/introduction-digital-humanities

These learning materials consist of a two-course module that seeks to provide humanities majors with a basic understanding of language technology and the practical skills needed to apply language technology using Python. The module is intended to empower the students by showing that language technology is both accessible and applicable to research in the humanities.

Taken from: Teaching with CLARIN 

https://www.clarin.eu/content/applied-language-technology 

Service based on Jupyter Notebook enables the creation and sharing of documents containing “live” code, equations, visualisations and texts. It allows to write simple programs, numerical simulations, statistical modeling, data visualization and much more.

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.

This source includes a series of resources in the form of guides and e-books dedicated to trainers and students interested in sample design, weighting, changes over time using cross sectional and longitudinal data and mapping census data using different software.

EOSC-Synergy training platform is set of tools for the creation and conduction EOSC related training courses. It facilitates cloud related courses providing tools for interactive computing. The platform is based on the container’s technologies, that allows for combining together in a suitable learning setup for students/training participants.

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.