 | Study programme 2023-2024 | Français | |
 | Probability and Statistic | ||
Programme component of Bachelor's in Computer Science (MONS) (day schedule) à la Faculty of Science |
| Code | Type | Head of UE | Department’s contact details | Teacher(s) |
|---|---|---|---|---|
| US-B3-SCINFO-002-M | Compulsory UE | GROSSE-ERDMANN Karl | S844 - Probabilité et statistique |
|
| Language of instruction | Language of assessment | HT(*) | HTPE(*) | HTPS(*) | HR(*) | HD(*) | Credits | Weighting | Term |
|---|---|---|---|---|---|---|---|---|---|
| Français | 29 | 13 | 3 | 0 | 0 | 4 | 4.00 | 1st term |
| AA Code | Teaching Activity (AA) | HT(*) | HTPE(*) | HTPS(*) | HR(*) | HD(*) | Term | Weighting |
|---|---|---|---|---|---|---|---|---|
| S-MATH-030 | Introduction to R | 3 | 0 | 3 | 0 | 0 | Q1 | |
| S-PHYS-101 | Probability and Statistics | 26 | 13 | 0 | 0 | 0 | Q1 |
| Programme component | ||
|---|---|---|
 | US-B2-SCINFO-004-M Probability | |
Objectives of Programme's Learning Outcomes
- Understand the fundamentals of computer science
- Use the vocabulary and the correct mathematical reasoning to formulate and solve problems in the field of computer science
- Demonstrate basic knowledge and know-how in related fields
- Demonstrate knowledge and basic skills in science and technology.
- Understand the fundamentals related to scientific methods
- Conduct rigorous reasoning based on scientific arguments
- Give a critique and argue a point of view regarding multiple-source information and other opinions
- Understand the fundamentals of communication
- Communicate information (both orally and in writing) relating to the field of computer science in an intelligible, clear and structured way
- Communicate a consistent and rigorous scientific argument, either orally or in writing
Learning Outcomes of UE
Introduction to the statistics software R. More on probability and an introduction to statistics
UE Content: description and pedagogical relevance
Introduction to the statistics software R.
Probability:
- limit theorems
- quantiles, simulation
Statistics
- estimator
- confidence intervals for gaussian samples
- hypothesis tests for gaussian samples
- t-test for two samples
- Chi-squared tests
- linear regression
Prior Experience
Basic notions of probability
Type(s) and mode(s) of Q1 UE assessment
- Written examination - Face-to-face
- Practical exam - Face-to-face
Q1 UE Assessment Comments
The theoretical part of the course will be evaluated by a written exam. The statistical work on data will be evaluated by a test using R.
Method of calculating the overall mark for the Q1 UE assessment
Not applicable
Type(s) and mode(s) of Q1 UE resit assessment (BAB1)
- N/A - Néant
Q1 UE Resit Assessment Comments (BAB1)
Not applicable
Method of calculating the overall mark for the Q1 UE resit assessment
Not applicable
Type(s) and mode(s) of Q3 UE assessment
- Written examination - Face-to-face
- Practical exam - Face-to-face
Q3 UE Assessment Comments
The theoretical part of the course will be evaluated by a written exam. The statistical work on data will be evaluated by a test using R.
Method of calculating the overall mark for the Q3 UE assessment
Not applicable
Type of Teaching Activity/Activities
| AA | Type of Teaching Activity/Activities |
|---|---|
| S-MATH-030 |
|
| S-PHYS-101 |
|
Mode of delivery
| AA | Mode of delivery |
|---|---|
| S-MATH-030 |
|
| S-PHYS-101 |
|
Required Learning Resources/Tools
| AA | Required Learning Resources/Tools |
|---|---|
| S-MATH-030 | Slides of the presentation put on moodle Exercise sheets |
| S-PHYS-101 | Exercise sheets |
Recommended Learning Resources/Tools
| AA | Recommended Learning Resources/Tools |
|---|---|
| S-MATH-030 | Not applicable |
| S-PHYS-101 | Not applicable |
Other Recommended Reading
| AA | Other Recommended Reading |
|---|---|
| S-MATH-030 | Not applicable |
| S-PHYS-101 | Not applicable |