The first part of the course focuses on the fundamental concepts necessary to understand probability calculation. The calculation of probabilities, seen as a science of uncertainty and variability, aims to predict in situations where not everything is perfectly predictable, situations that can be found in all engineering sciences such as measurement uncertainties, quality control, equipment or communication reliability. The purpose of the statistical part is to allow the practitioner (decision-maker, etc.) to determine his position in the most reasoned way possible according to the context and the data available or that can be acquired.
| On completion of the unit, the student will be capable of: | Classification level | Priority |
|---|---|---|
| Use basic tools, including the concepts of random variables, probability distributions, independence, moments (such as expectation and variance for example) | 2. Understand | Essential |
| Be able to make point and confidence interval estimates for parameters of the usual laws from statistical sample data. | 3. Apply | Essential |
| Perform simple linear regression models, compare and critique them | 4. Analyse | Essential |
| Implement the methods and models studied under the R software | 3. Apply | Important |
| Write a clear and concise report on a data processing operation (such as estimation or regression) | 5. Summarise | Important |
| Percentage ratio of individual assessment | Percentage ratio of group assessment | ||||
|---|---|---|---|---|---|
| Written exam: | 70 | % | Project submission: | 0 | % |
| Individual oral exam: | 0 | % | Group presentation: | 0 | % |
| Individual presentation: | 0 | % | Group practical exercise: | 30 | % |
| Individual practical exercise: | 0 | % | Group report: | 0 | % |
| Individual report: | 0 | % | |||
| Other(s): 0 % | |||||
| Type of teaching activity | Content, sequencing and organisation |
|---|---|
| Course | Probabilities, conditional probabilities, independent events |
| Practical work | Getting to grips with the R software |
| Case study | Study of real data sets using statistical methods such as linear regression or factor analysis. |
| Supervised studies | Law calculations, methods for simulating random variables, estimation of the parameters of a probability law |