Learning Results
1.Knowledge of the probability models that constitute the foundations of statistical inference and decision
making.
2.Knowledge of the most important concepts of statistical inference.
3.Application of the main inferential statistical methods.
4.Application of appropriate statistical techniques to obtain conclusions that help decision making at various
levels in contexts of uncertainty.
Program
1.Descriptive statistics
2.Introduction to the Theory of probability
3.Random variables
4.Probability distributions
5.Sampling. Sampling theoretical distributions
6.Point estimation: estimation methods, properties of estimators
7.Interval estimation
8.Parametric statistical tests
9.Non-parametric tests
Internship(s)
NAO
Bibliography
Murteira, B., Ribeiro, C.S., Silva, J.A. and Pimenta, C., Introdução à Estatística, McGraw-Hill (2002)
Pestana, D. and Velosa, S., Introdução à Probabilidade e Estatística, Fundação Calouste Gulbenkian (2002)
Pedrosa, A.C. and Gama, S.M., Introdução Computacional à Probabilidade e Estatística, Porto Editora (2004)
Newbold, P., Carlson, W. and Thorne, B., Statistics for Business and Economics, Prentice Hall (2002)
Webster, A.L., Applied statistics for business and economics-an essentials version, McGraw-Hill (1998)