Data analysis and visualisation
- Statistical data analysis in R, SAS, SPSS / PSPP or STATA: evaluation of data and surveys, calculation of descriptive and explorative statistics, evaluation of complex data sets / Big Data (e.g. routine data / secondary data in health care, ImmobilienScout24) and small-scale data analyses (in R, SAS, Quantum GIS).
- Data visualisation: graphical presentation of results (ggplot2, plotly), visualisation of spatial data (e.g. Leaflet), interactive web applications / dashboards in R (Shiny Apps: shinydashboard / Flexdashboard).
- Development of data products: Automated data processing, data visualisation development and automated reporting (RMarkdown / Sweave / LaTeX).
- Data preparation, structuring incl. data checking, cleansing and validation (data manipulation / wrangling).
- Data mining: identification of patterns, classification, clustering, regression.
- Projections and forecasts (e.g. household forecasts).
- Training and education on data analysis with R: basic training and individual, practice-oriented training, programming of swirl course units.
- Conception of teaching / training materials (classic and e-learning), case studies and exercises.
- Consultation on scientific questions, especially with a (socio-)demographic or health prevention focus, e.g.:
- What effects does demographic change have on the health care system (including burden of disease, need for care, prevention, jobs in the health and care sector, care facilities)?
- What changes does demographic change bring for the social sector (day care facilities, education)?
- What are the consequences of demographic change for the labour market (e.g. number of people in employment, age structure of the workforce in companies, shortage of skilled workers)?
- How do areas differ in terms of socio-structural characteristics? Which city-wide developments can be observed?
- Empirical studies: Advice on the planning and implementation of quantitative projects.
- Survey advice: Advice on the choice of survey mode, the design of questionnaires, the realisation of surveys, data collection and processing.
- Advice on statistical data evaluation, visualisation and communication of results.
