2017-2018 / MATH0487-2

Elements of statistics

Duration

15h Th, 10h Pr, 25h Proj.

Number of credits

 Bachelor in engineering3 crédits 
 Bachelor in computer science3 crédits 
 Master in data science (120 ECTS)3 crédits 
 Master in data science and engineering (120 ECTS)3 crédits 

Lecturer

Louis Wehenkel

Language(s) of instruction

French language

Organisation and examination

Teaching in the first semester, review in January

Units courses prerequisite and corequisite

Prerequisite or corequisite units are presented within each program

Learning unit contents

  • Link between probability and statistics
  • Data generation and exploration
  • Parametric estimation and confidence intervals
  • Hypothesis testing
  • Association methods

Learning outcomes of the learning unit

The student will understand the fundamental principles of statistics, and he will be able to apply them to carry out exploratory data analyses, population parameter estimation, and hypothesis testing. He will also understand the nature of regression and variance analysis problems, as well as the interest of non-parametric methods.

Prerequisite knowledge and skills

Calculus, algebra, geometry and probability. Elements of computer science and applied mathematics.

Planned learning activities and teaching methods

Theory is given via 6 lectures, in French. This is completed by exercise sessions (5) and by a practical project. The project will lead the student from exploratory data analysis towards parameter estimation and hypothesis testing, all this based on a real-life dataset of interest to the student. The project will be carried out by groups of two students, is mandatory, and its evaluation counts for 25% of the final grade.

Mode of delivery (face-to-face ; distance-learning)

Face-to-face

Recommended or required readings

Students will have access to the slides used for the theory lectures and exercise notes.
Regarding the theory part, see http://www.montefiore.ulg.ac.be/~lwh/Stats/ Regarding the exercise and practical projects, see http://www.montefiore.ulg.ac.be/~lduchesne/stats

Assessment methods and criteria

The note is composed of two parts: the practical projects (25% of the final note) and a written exam. The latter is composed of three parts: the theory (25% of the final note), a question about the project (5%), and exercises (45% of the final note).

Work placement(s)

No training

Organizational remarks

2013-2014 corresponds to the first instance of this new version of the course.

Contacts

Professor: Louis WEHENKEL (L.Wehenkel@ulg.ac.be)
Main Assistant: VAN LISHOUT François (L.Duchesne@ulg.ac.be)
Please contact us by email, using the following subject: "course: Elements of statistics". We will then fix an appointment to meet at Montefiore if necessary.