Topic outline

  • Introduction to Statistics with Python

    Streamed from Basel, 21-22 June 2021


    Links for the course:

  • Programme

    Day1 : 

    09-12 : python warmup; data exploration and visualization

    13-17: statistical distributions and testing : core concepts behind statistical testing and applications (t-test, normality test)


    Day2 :

    09-12 : presentation of some common tests (fisher's exact test, chi square, ANOVA, ...)

    13-17 : correlation and regression analysis : linear models


    • Course material & software install

      Please do make sure you have python3, jupyter, scipy, as well as the statsmodels library ( https://www.statsmodels.org/stable/install.html)installed. Contact us IN ADVANCE if you have trouble with the installation. 

      In our experience, trainees tend to gains more out of this course when they are at ease with python. 

      Although it is by no mean mandatory, I would recommend you practice a little bit of python coding in the days before the course, as a form of pre-warmup. If you have no idea how to practice, we can recommend https://www.w3resource.com/python-exercises/basic/, whose interactive corrections are quite enjoyable.


      • Exam