Mathematics for the statistician - Introduction to probability and statistics.

lstat2010  2017-2018  Louvain-la-Neuve

Mathematics for the statistician - Introduction to probability and statistics.
8 credits
30.0 h + 45.0 h
Q1
Teacher(s)
de Lannoy Gaël; Desmet Lieven; Van Keilegom Ingrid;
Language
French
Aims

At the end of this learning unit, the student is able to :

1

By the end of the course, the student will be familiar with the basis of mathematics, probability and statistics, necessary to start the courses of methodology and practice of statistics of the program.

 

The contribution of this Teaching Unit to the development and command of the skills and learning outcomes of the programme(s) can be accessed at the end of this sheet, in the section entitled “Programmes/courses offering this Teaching Unit”.
Content
Content PART I : Mathematics : Analysis of functions, limits, continuity, derivatives, integrals, matrix algebra. Part II : Probability : Event, probability and conditional probability, Bayes theorem, discrete and continuous random variables, particular laws, density function, distribution function, moments, random vector, limit theorems. PART III : Statistics : Point estimation, confidence interval and hypothesis testing with application to the case of normal population(s) or proportions. Teaching methods The course consists of lectures and exercise sessions.
Bibliography
  • Dowling, E.T. (1995). Mathématique pour l'économiste. McGraw-Hill, London.
  • Droesbeke, J.-J. (1997). Eléments de Statistique. Editions de l'Université de Bruxelles & Editions Ellipses.
  • Khuri, A (1993). Advanced calculus with applications in statistics, Wiley, New York.
  • Wackerly, D.D., Mendenhall, W. et Scheaffer, R.L. (1996). Mathematical Statistics with Applications, 5th Ed , ITP, Duxbury Press.
Faculty or entity
LSBA