2017-2018 / MATH0482-3

Probability and statistics II

Duration

30h Th, 15h Pr, 5h Mon. WS

Number of credits

 Bachelor in mathematics5 crédits 

Lecturer

Yvik Swan

Language(s) of instruction

English language

Organisation and examination

Teaching in the second semester

Units courses prerequisite and corequisite

Prerequisite or corequisite units are presented within each program

Learning unit contents

  • Probabilities on a finite set
  • Notions of measure theory
  • Random variables and random vectors
  • Expectation
  • Sequences of random vectors and convergence modes
  • The central limit theorem
  • Conditionnal expectation
  • Limit theorems

Learning outcomes of the learning unit

At the end of the course the student will have a deep understanding of the concepts at the heart of probability theory. He will know the fundamental probability distributions and will be able to competently assess any risk. 

Prerequisite knowledge and skills

A good mastery of calculus is indispensable to follow this class. 

Planned learning activities and teaching methods

Ex cathedra classes as well as exercise sessions. 

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

Recommended or required readings

Complete course notes (including exercise sets) will be made available through MyULg before the course. 
Bibliography

  • Billingsley, P. (2008). Probability and measure. John Wiley & Sons. [Casella and Berger, 1990] Casella, G. and Berger, R. L. (1990). Statistical inference, volume 70. Duxbury Press Belmont, CA.
  • Cheng, S. (2008). A crash course on the lebesgue integral and measure theory.
  • Durrett, R. (2010). Probability : theory and examples. Cambridge Uni- versity Press.
  • Feller, W. (2008). An introduction to probability theory and its applications, volume 2. John Wiley &amp ; Sons.
  • Lawler, G. F. (2011). An introduction to the mathematical foundations of probability theory.
  • Pollard, D. (2002). A user's guide to measure theoretic probability, vo- lume 8 of Cambridge Series in Statistical and Probabilistic Mathematics. Cambridge University Press, Cambridge.
  • Ross, S. and Peköz, E. (2007). A second course in probability. ProbabilityBookstore. com.
  • Ross, S. M. (2010). A first course in probability. Pearson Prentice Hall. [Rudin, 2006] Rudin, W. (2006). Real and complex analysis. Tata McGraw-Hill Education.
  • Van Gelder, P. (1996). A new statistical model for extreme water levels along the dutch coast. Stochastic Hydraulics, 96 :243-249.
  • Williams, D. (1991). Probability with martingales. Cambridge university press.

Assessment methods and criteria

The first and second session exams will contain theoretical questions (some of which are announced in class) and exercises inspired by those studied during the year.  

Work placement(s)

Organizational remarks

The course is taught in English, although examination is in French. 

Contacts

Yvik Swan  Département de Mathématique, Grande Traverse, 12, Sart Tilman, B-4000 Liège +32 4 366 94 76 yswan at  ulg.ac.be