| Course label : | Industrial Statistics |
|---|---|
| Teaching departement : | MIN / Applied Mathematics and General Computing |
| Teaching manager : | Mister VINCENT LEDDA |
| Education language : | French |
| Potential ects : | 0 |
| Results grid : | |
| Code and label (hp) : | IE4_ADAD_MIN_SIN - Statistiques industrielles |
Education team
Teachers : Mister VINCENT LEDDA / Mister AUGUSTIN MOUZE
External contributors (business, research, secondary education): various temporary teachers
Summary
The goal of this training is to help the engineer and the manager to decide in a context of uncertainty by controlling the risks taken. On the one hand, it is important to identify the uncertainties he/she faces and on the other hand to make the best possible decisions for levels of risk that are measured and accepted by the company, its suppliers and its customers. Mathematical statistics offer a whole range of tools to do this. At the end of this training the student will know the principles and the most common uses. He will also have the knowledge to identify and appropriate those that will be needed in the exercise of his future profession.
Educational goals
The student will be able to - Master the statistical inference process: understand and analyze the company's data in its environment: identify, quantify and characterize its products and services for diagnostic and management purposes. - Understand and master the problem of quality assurance in the customer-supplier relationship throughout the supply chain, both online and offline; - Model experimentaly processes or phenomena in order to optimize or control them. - Master the reliability of products and services: understand, model, measure, document. Analyze their failure modes and criticalities. Contribution to the competency framework (consult the RNCP): The student will have progressed in his abilities to: - Analyze a market, customer needs, competition - Develop a marketing plan - Define the characteristics of a product and design the production methods according to production requirements - Track a product or product line, advocate for improvements - Perform the interface between the customer and the departments of the company
Sustainable development goals
Knowledge control procedures
Continuous Assessment
Comments: 2 continuous assessment notes, each counting for 50%, the first in the middle of the intervention, the other at the end. These are exercises done during session using Excel and deposited in pedagogical platform Moodle.
Online resources
Excel for implementation and statistical calculations Moodle pedagogical platform including course materials, exercise statements and answers
Pedagogy
The focus is on problem solving. Courses and exercises are offered as the program progresses.
Sequencing / learning methods
| Number of hours - Lectures : | 8 |
|---|---|
| Number of hours - Tutorial : | 12 |
| 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) : | 0 |
| 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
Mathï¿œmatiques 4, IE2_MATH_M&I_MA4
Maximum number of registrants
Remarks
See Moodle platform for a detail content.