Quantitative data analysis

easySHARE is a simplified HRS-adapted dataset for student training, and for researchers who have little experience in quantitative analyses of complex survey data. While the main release of SHARE is stored in more than 100 single data files, easySHARE stores information on all respondents and of all currently released data collection waves in one single dataset. Moreover, for the subset of variables covered in easySHARE, the complexity was considerably reduced. For example the information collected only from one person of a couple or in a household was transferred to all respective respondents; time constant information collected only in the first interview was transferred to all later interviews; the coding of missing values was enriched to provide an easier understanding of the routing and filtering of the interviews; etc. In addition, several ready to analyse variables have been added, such as health indexes, demographic information, or economic measures. When possible measures have been selected or recoded to facilitate comparative analyses with the US Health and Retirement Study (HRS).

In this era of evidence-driven reform, school leaders must learn to harness an array of data to drive improvement. In this module, you will explore key concepts in performance measurement, research design, and data analysis (qualitative and quantitative) to understand what can be gleaned from different sources. With your cohort, you will discuss the data you have available and learn how to draw on multiple forms of evidence to make more informed policy and programmatic decisions.

Youtube playlist of past webinars organised by the UK Data Service. Topics include:

• mapping crime data in R
• longitudinal data
• census and population data
• getting started with secondary analysis
• data management
• how to anonymise quantitative and qualitative data
• working with twitter data
• web scraping
• consent issues in data sharing

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 is a list of literary corpora that are available as part of the CLARIN Resource Families initiative.

Literary corpora comprise poetry and fictional prose texts, such as novels, short stories and plays. They bring together the collected works of a single author or representative from a specific literary period. Since the literary corpora are often available through powerful concordancers, they are especially well suited for a quantitative and qualitative approach to comparative literary analysis, within or across different genres and historical periods.

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

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.

Research is getting a global makeover, in part thanks to the power of the internet and the tools it provides for us, and in part due to a growing call for accountability (e.g., reproducibility and data provenance) in research. Global policies are emerging at different levels that include some aspect of Open Research, Open Scholarship, or Open Science, and inclusive of all research disciplines. But our universities are often letting us down, and they are not teaching us the knowledge, tools and skills we need to do research effectively in the 21st century.

“Open Science” has many interpretations, but at its core it is about increased rigour, accountability, and reproducibility for research. For us, it is based on the principles of inclusion, fairness, equity, and sharing. Open Science can be viewed as research simply done properly, and it extends across the Life and Physical Sciences, Engineering, and Mathematics, to Social Science and Humanities.

This MOOC is designed to help equip students and researchers with the skills they need to excel in a modern research environment. It brings together the efforts and resources of hundreds of researchers and practitioners who have all dedicated their time and experience to create a community to help propel research forward.