Statistics

Provide students with 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
- Process data, implement and interpret statistical tests to make decisions.
Data will be processed with R software via the RStudio development environment.

Basic elements of probability calculus

Part I
Introduction
1 Descriptive statistics
1.1 Univariate descriptive statistics
1.2 Bivariate descriptive statistics
2 Reminders of probability: usual laws (binomial law, normal law, etc.)
3 Sampling and estimation
3.1 Principle of sampling
3.2 Qualities of an estimator
3.3 Confidence intervals (means, variance and proportions)
3.4 Sample size
4 Introduction to hypothesis testing
4.1 General information: principle of hypothesis testing
4.2 Compliance tests: mean, proportion, variance
4.3 Goodness-of-fit tests
4.4 Tests of independence
4.5 Notion of power
5 Linear regression
5.1 Principles
5.2 Least squares criterion
5.3 Evaluation of fit
5.4 Estimates and associated hypothesis tests

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.
Dodge Y, [2006]. Premiers pas en statistiques, Springer.