Statistics

Give students an essentially practical knowledge of basic statistical tools: - summary presentation of results, numerical and graphical - analysis of these results, possible conclusions in terms of estimates or tests
At the end of the course, students should be able to:

Know the potential of the
method Know how to encourage the use of such a tool when useful
Understand the vocabulary and implications of statistical analysis results

Basic elements of probability calculus

Introduction and definitions
Description of results

Descriptive statistics for one variable (mean, standard deviation, variance).
Descriptive statistics for two variables (fit, linear regression).


Probability laws

Binomial laws, Poisson laws
Normal law and Student's law.


Outlier tests and goodness-of-fit tests

Grubbs' test and Cochran's test.
Chi-square test and Kolmogorov's test.


Confidence intervals

Chi-square law and Fisher's law.
Confidence intervals for mean and variance
Confidence intervals for proportions (large samples).

Engineering Sciences and Techniques

Dagnelie P. [2007]. Theoretical and applied statistics. Tome 1. Descriptive statistics and foundations of statistical inference. De Boeck et Larcier.
Dagnelie P. [2006]. Theoretical and applied statistics. Tome 2. One- and two-dimensional statistical inference. De Boeck et Larcier.
Saporta G. [2006]. Probabilités, analyses des données et statistiques, Technip.