Causal Statistics & Bayesians

Rigorous data-science for students, researchers and companies

I help you draw rigorous conclusions from your data, favoring causal and Bayesian models. Whether for data analysis, research projects or internal studies, I put my skills at your service.

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SERVICES

Consulting Service

Personalized support, from methodological design to the performance of exploitable results.

Methodology

Assistance in study design, choice of sampling plans, definition of models, definition of variables and measurements.

  • Documentation and transparency of choices
  • Observational and experimental studies
  • Randomization, controls, analysis plans

Data preparation

Cleaning, structuring, harmonizing and integrating your data before analysis.

  • Preparation for causal and Bayesian analyses
  • Creating data pipelines
  • Documentation and reproducible scripts

Support for articles and theses

Revision of the Statistics section, method recommendations, assistance in drafting results and interpreting.

  • Methodological journals for scientific journals
  • Doctoral and Master theses

Causal data analysis

Modeling of treatment effects, causality under observation conditions, reduction of selection bias.

  • Predictor adjustment models (regression, matching)
  • Propensity score models, difference-of-differences
  • Prudent interpretation of causalities

Bayesian modeling

Individual courses or sessions or in groups adapted to your needs on statistics, causality or Bayesian models.

  • Hierarchical and multilevel models, like Mixed Marketing Model
  • Visualization and communication of post-post distributions

Training and coaching

Individual courses or sessions or in groups adapted to your needs on statistics, causality or Bayesian models.

  • Practical workshops with Python/R
  • Preparing to analyze your own projects
  • Support for adoption of new methods

See training

CONTACT

Why Bayesian statistics and causal methods?

Bayesian statistics are more intuitive and have lessa priori that classic frequentist statistics, although theIntuition wants us to believe otherwise. In addition, they allowobtain answers generatively as much whenThere are differences only whenhe nthere is none. The classic statistics are content to give an answer in case of differences. Otherwise, the decision is suspended. This greatly limits discoveries and leads to well-known dubious scientific behaviors now.

With regard to causal methods, firstly, they push to conceptualize experiments and analyzes more finely because of the representation of thean effect. Then, these methods allowPerform virtual experiments where it doesis not possible in the real world, whether for ethical or statistic reasons (random impossible sampling). Finally, they provide indications on what sis produced, what could have happened (what if…?) and on what will happen.

PROFILE

Indicative rates

Rates are indicative and may vary depending on complexity, duration and volume of work. Personalized quotes are offered on request.

students

from 70 CHF/h

For methodological help, courses, interpretation, analytical proofreading and occasional support.

  • Choice of statistical test and analysis plan
  • Assistance in interpreting the results
  • Short formats or targeted packages

individuals

from 130 CHF/h

For research projects for individuals or academics. Support and analysis of non-commercial data

  • Statistical analysis, study design and reporting
  • Support SAS, R, Python, SQL as needed

company

from 150 CHF/h

For freelancers, firms or SMEs requiring advanced modeling or with a high business challenge.

  • Causal inference, Bayesian models, Expert audit
  • Strategic support
  • Implementation of AI systems (Machine Learning and LLM)
CONTACT

No more status quo with your data

Contact

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Useful information

Working area:
Switzerland (possible remote support)

Languages:
French, English, Italian (basic knowledge) and German (basic knowledge)