Workshops & Courses


Basic Statistics and Experimental Design with R, School of Cognition, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, 9th and 16th April 2021. It was successful.

Basics statistics and hands-on data analysis with R, Institute of Educational Sciences, University of Basel, 20 and 27 November 2020. The online workshop for Doctorate candidates and Post-doctorates was successful (see Testimonials).

On the 13th of March and the 16th of April 2020, I conducted a 2-day workshop: Basics statistics and hands-on data analysis with R. The workshop was dedicated for Doctoral candidates and Postdocs of University of Basel under the Graduate Center (GRACE) platform. It was successful (see Testimonials). The workshop introduced the following topics:

  1. Statistical thinking, an introduction
  2. Making sense of data (aka Exploratory Data Analysis)
  3. Introduction to R
  4. Introduction to Probability
  5. Making inference: statistical estimation
  6. Making inference: statistical testing
  7. Designing an experiment
  8. Wrap up & beyond 𝑡 test.

Hands-on Data Analysis with R, University of Neuchatel, CUSO, 10 May 2016. We analyzed three data sets (from the participants) that lead to the following topics:

  1. Welcome and Road Map
  2. Linear and Piecewise Linear Regression
  3. Prediction: GLM and Feature Selection
  4. Two Way ANOVA with Repeated Measures,

and when you are interested in the R codes, simply contact me. The workshop was excellently organized and very successful  (see also Testimonials). Participants rated it with increasing number ranging from 1 to 5 with the following median (max). General rate is 4 (5), helpfulness of provided slides and R-scripts is 5 (5), presenting clarity is 4 (5).

To download the slides for the four topics above:

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On the 11-12 May 2015, I conducted a 2-day workshop: Applied Statistics for Computer Scientists, with R. The 2-day workshop was dedicated for Ph.D. students and postdocs of the Computer Science of CUSO (Conférence Universitaire de Suisse Occidentale), the conference of western universities in Switzerland: Bern, Fribourg, Geneva, Lausanne and Neuchâtel. It was very successful (see Testimonials). The workshop introduced the following topics, together with R implementation for statistical computing and graphics:

  1. Data Analysis & Production
  2. Introduction to Probability
  3. Foundations for Statistical Inference
  4. Two-way Table & ANOVA
  5. Multiple linear regression
  6. Multiple Logistic Regression.

Courses I have taught for Coaching

Introductory Courses

  • Mathematics (the science of quantity, structure, space and change): arithmetic, algebra, geometric, analysis, optimization
  • Probability (the analysis of random phenomena)
  • Statistics (the study of collection, organization, analysis, interpretation & presentation of data)
  • Programming with R
  • Data visualization with R

Advanced Courses

  • Biostatistics
  • Quantitative Methods
  • Time Series Econometrics
  • Multivariate Analysis
  • Mathematics for Underwriter
  • Mathematics for Reinsurance
  • Probability/Measure Theory
  • Probability Modeling
  • Stochastic Processes
  • Statistical Inference
  • Computational Statistics (with R)
  • Mathematical Statistics

Special Topics

  • Hypothesis Tests (parametric & nonparametric)
  • General Linear Model (the errors follow Gaussian, the relationship is linear): Multiple Linear Regression, ANOVA
  • Generalized Linear Model (the errors are NON-Gaussian, the relationship is linear)
    • Bernoulli, Binomial, Multinomial, Poisson, Negative Binomial, Exponential, Gamma (GLM)
    • Fixed Effect, Random Effect (GLMM)
  • Generalized NON-Linear Model (the errors are NON-Gaussian, the relationship is NON-linear)
  • Discrete Time Series: ARIMA, VAR
  • Continuous Time Stochastic Processes
  • Maximum Likelihood Estimation (MLE)
  • Empirical Risk Minimization
  • Conditional Expectation
  • Statistical Learning