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Probability and Statistics

• 30 h - Lectures (15h), tutorial class (15h)
• Experimental project : no
• Description:
• Descriptive statistics:

- Uni-variate data: quantitative / qualitative, distribution (frequency and cumulative) mean/mode/median, standard deviation, inter-quartile range, whisker plot

- Bi-variate data: scatter plot, covariance, Pearson and Spearman coefficients, linear fit to data.

- Data manipulation with python

- Chi2 test

• Theory of probabilities:

- Sample space, events, probabilities, the art of counting

- Conditional probabilities, independence

- Random variables: dicrete / continuous, law (PDF/CDF), expectancy, mean/mode/median, variance/covariance, normal laws and estimation.

• Description: Théorie des probabilités, variables aléatoires, lois statistiques, estimateurs, techniques multivariées.