Statistics Training

SCILAB training course for statistics

You might not be familiar with the numerical concept of statistics, but I am pretty sure your daily work requires you to:

  • Evaluate and describe the numerics of your product or process
  • Try to infer a model based on some measurements or analytical data


Training objective

Provide you with the basics to be able to:

  1. Summarize your dataset through a few descriptive variables and infer a statistical model
  2. Understand some basics on statistics theory and its numerical implementation
  3. Qualify your problem to choose the most efficient method to solve it
  4. Discover different methods implemented in Scilab and make efficient use of 



Training content

Basic data analysis
Introduction to statistics problem in real life

  • Data mining

  • Data fitting

  • Descriptive Statistics

Numerical setting
Introduction to statistics problem in mathematics & numeric

  • Regression

  • Classification

  • Clustering

The Design of Experiments
Introduction to appropriate sampling of data from measurement or simulation
(Factorial design, Box-Benhken, Central composite design, Latin Hypercube Sampling,...)
  • Design techniques
  • Experiment purpose
  • Design purpose

Meta-modeling & Validation

Response Surfaces, Kriging, POD/SVD, Radial Basis Functions,...



Training duration

Depending on your mathematical level:

  • Beginner (3 days)
    We will take 2 days for the theoritical content to be sure you master the basis and one day to explore the exercises
  • Intermediate (2 to 3 days)
    We can take only 1 day for the theoritical content, focus on the exercise on another day. If you are interested in more dedicated Scilab experience, you can also provide us with one of your use case that we will investigate together on one more day.