What we do
Services
Planning a study
Before you collect data, we help you design your study so that your research question can be addressed in the best possible way. We also determine the minimal sample size for which a given effect, if present, has high probability of being detected (power analysis).
Preprocessing data
We consolidate data sets, clean them of errors, perform sanity checks and identify potential outliers. We recode problematic values, reshape tables and build convenient data structures.
Empirical data analysis
Get a feel for your data: We compute common statistics, discover underlying patterns and dependences and find meaningful low-dimensional representations of high-dimensional data.
Model building
We build the simplest viable model for your research question and choose suitable statistical procedures. Based on the outcomes, we iterate and refine.
Fitting and diagnosing models
We find the best model parameters and probability distributions, test goodness-of-fit and perform sensitivity analyses. We compute p-values and confidence intervals or Bayesian credible intervals where appropriate.
Checking and advice
We verify and validate your existing data science pipeline. Does your academic discipline follow a certain protocol? Has your company used a certain procedure for years? Did an AI propose a certain path or perform a complete analysis? We offer an objective second opinion as well as hands-on advice on how to move forward.
R packages & Shiny apps
We create custom R tools: from tailor-made functions and packages (with C++ code underneath for complex computations) to shiny apps for dashboards, reporting and education.
Reporting and visualization
We create reports with as much or as little technical detail as you require. We provide you with text modules for proposals, research papers or business reports. We create convincing visualizations to communicate findings true to your data.
Courses and trainings
We teach what we know. Whether it is in a course, a workshop or an individual training. From the basics in statistics and R to specialist knowledge in spatial statistics, optimal transport and statistical programming.