Probability and Statistics

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Objectives

In this curricular unit an introduction to Probability Theory and Statistical Inference, in its parametric version, is given.

The student should be able to do an exploratory data-analysis, apply correctly the probabilistic models studied and perform statistical analysis, specially when normal populations are involved.

Program

An Introduction to the R Language. Exploratory Data-Analysis. Fundamental Concepts of Probability. Random Variables and Random Vectors. Discrete and Continuous Probability Distributions. Random Sampling. Point Estimation. Confidence Estimation. Testing of Hypothesis. An Introduction to Simple Linear Regression.

Teaching Methodologies

The theory classes will have an expository component, always accompanied by some application examples. The teacher/student interaction will also be an important component in both theory and practice classes. In the latter, the student will have a first contact with the statistical package R (open source), which will be used to perform statistical analyses throughout the semester.

Bibliography

Baron, M. (2007). Probability and Statistics for Computer Scientists. Chapman & Hall/CRC, Boca Raton.

Guimarães, R.C. e Cabral, J. A. S. (2011). Estatística, 2ª ed., Verlag Dashofer, Lisboa.

Montgomery, D.C. and Runger, G.C. (2003). Applied Statistics and Probability for Engineers, Wiley, New York.

Pestana, D.D. e Velosa, S.F. (2006). Introdução à Probabilidade e Estatística, Vol. I., 2ª ed., Fundação Calouste Gulbenkian, Lisboa.

Code

01060895

ECTS Credits

6

Classes

  • Teóricas - 40 hours
  • Teórico-Práticas - 20 hours

Evaluation Methodology

  • According to CU programme: 100%