| Course label : | Applied statistics |
|---|---|
| Teaching departement : | CMA / |
| Teaching manager : | Mister LUDOVIC THUINET |
| Education language : | |
| Potential ects : | 0.0 |
| Results grid : | |
| Code and label (hp) : | ENSCL_CI_M5_4_1 - Stat. appliq. |
Education team
Teachers : Mister LUDOVIC THUINET
External contributors (business, research, secondary education): various temporary teachers
Summary
The purpose of this course is to present statistical methods and laws allowing in practice to set up procedures for controlling the quality of a batch, to determine the probability law of a reference population from a sample, to carry out comparison tests between several populations and to associate confidence intervals with these operations.
Educational goals
1/ Use the concept of probability associated with discrete or continuous random variables to construct a certain number of models that can account for concrete situations, where the application of deterministic laws is impossible. Particular attention is paid to the concepts of mathematical average, variance and the operations attached to them. 2/ Present the normal law which is the probabilistic model most used to describe many phenomena observed in practice. 3/ Introduce the concepts of population and sample and implement statistical control procedures to determine the quality of a batch. 4/ Explicitly determine the probability law defining a reference population from a sample (statistical inference). 5/ Carry out statistical comparison tests between several populations. 6/ Define the least squares line and calculate its statistical properties.
Sustainable development goals
Knowledge control procedures
Continuous Assessment
Comments: 1 final written exam (duration: 1h30)
Online resources
1 handout of statistics course including the statements of the exercises covered in tutorials. 1 booklet containing the numerical tables associated with the usual laws of probability. Online documentation in Moodle for independent work.
Pedagogy
In lectures, the basic concepts of statistics are covered: probability, discrete random variables, continuous random variables, statistical controls, statistical tests, statistical estimation, linear regression. Tutorial sessions are dedicated to exercises in the application of statistical methods seen in class.
Sequencing / learning methods
| Number of hours - Lectures : | 8 |
|---|---|
| Number of hours - Tutorial : | 4 |
| Number of hours - Practical work : | 0 |
| Number of hours - Seminar : | 0 |
| Number of hours - Half-group seminar : | 0 |
| Number of student hours in TEA (Autonomous learning) : | 3 |
| Number of student hours in TNE (Non-supervised activities) : | 0 |
| Number of hours in CB (Fixed exams) : | 0 |
| Number of student hours in PER (Personal work) : | 0 |
| Number of hours - Projects : | 0 |
Prerequisites
Mathematical integration, basic notions of probability