Probabilities
2
2022-2023
01001258
Mathematics
Portuguese
Face-to-face
SEMESTRIAL
6.0
Compulsory
1st Cycle Studies
Recommended Prerequisites
Infinitesimal Analisys I, II, III.
Teaching Methods
Lectures are expository, but also include examples and exercises to help grasping theory and gaining practical experience about the acquired knowledge. During the semester, students can also use tutorial time to discuss their ideas and clarify possible understanding difficulties.
Learning Outcomes
The development of this curricular unit takes into account the main guidelines of a basic course in Probability: to describe, analyze and interpret real-world situations through nondeterministic mathematical models and to provide the essential theoretical skills for subsequent studies in areas as Statistics or Stochastic Processes.
This course allows developing the following skills: ability to calculate; knowledge of mathematical results; ability to generalize and abstract; formulating and solving problems; design and use of mathematical models for real situations; writing and oral expression rigorous and clear. On a personal level, it allows to develop individual initiative, teamwork, research and independent learning.
Work Placement(s)
NoSyllabus
Chapter1 Introduction to probability theory. Basic probability theory: classical and frequentist approaches. Probability spaces. Conditional probabilities. Independence
Chapter2 Probability distributions on IR. Real random variable. Discrete probability distributions, absolutely continuous probability distributions and mixed probability distributions. Location and dispersion parameters: moments and quantiles
Chapter3 Probability distributions on IRn. Real random vectors. Discrete probability distributions, absolutely continuous probability distributions. Independent real random variables. Moments of real random vectors: mathematical expectation, variances-covariances matrix.
Chapter4 Characteristic function and random variables independence. Characteristic function and moments
Chapter5 Stochastic Convergences. Convergence in distribution. Almost sure convergence, convergence in probability and mean square convergence. Law of large numbers and central limit theorem.
Head Lecturer(s)
Carlos Manuel Rebelo Tenreiro da Cruz
Assessment Methods
Final Assessment
Exam: 100.0%
Continuous Assessment
Mini Tests: 30.0%
Frequency: 70.0%
Bibliography
E. Gonçalves, N. Mendes-Lopes, Probabilidades - Princípios Teóricos, 2ªed., Escolar Editora, 2013
K. I. Chung, A Course in Probability Theory and Mathematical Statistics. Academic Press, 1974
D. Foata and A. Fuchs, Calcul des probabilités, Masson, 1996
D. Pestana and S. Velosa, Introdução à Probabilidade e à Estatística, Vol. I, 2ª ed., Fundação Calouste Gulbenkian, 2006
S. Resnick, A probability path, I. Birkhauser, 1999
Ph. Tassi and S. Legait, Théorie des Probabilités en vue des Applications Statistiques, Éditions Technip, 1990