*)N.B. if there are students who do not speak Portuguese the language is English.
The objective of this course is to introduce a wide range of statistical and probabilistic tools used by civil engineers both in the professional practice and in research. After a review of basic material, the course covers some theoretical principles of random variable interaction. Statistical methods for designing experiments and analyzing data are also discussed. The last part of the course cover probabilistic techniques useful for decision-making under conditions of uncertainty, both to estimate parameters of models and in specific engineering applications. Examples are drawn from all areas of Civil Engineering – e.g., project management, environmental, transportation, with special emphasis on territorial planning and management.
- Introduction: Review of Probability and Statistics Concepts - Functions of Random Variables - Confidence Intervals and Hypothesis Testing - Analysis of Variance and Design of Experiments - Monte Carlo Simulation - Estimation methods (Method of Moments, Maximum Likelihood, Bayesian Methods) - Regression Analysis - Other applications: Order Statistics and Probability of Extremes, Reliability and Risk - Multiple regression – model estimation (least squares, maximum likelihood) and testing. - Analysis of variance (ANOVA). - Spatial Autocorrelation analysis - Spatial regression (point and areal data). - Structural equations modeling. - Panel data - Applications to spatial planning.
Undergrad Statistical Methods (or equivalent).
Generic skills to reach
. Competence in analysis and synthesis; . Competence to solve problems; . Critical thinking; . Competence in autonomous learning; . Research skills; . Competence in organization and planning; . Competence in oral and written communication; . Competence in information management; . Adaptability to new situations; . Competence in applying theoretical knowledge in practice; (by decreasing order of importance)
- Acetatos utilizados nas aulas / Handouts from lectures - Guimarães Rui C & Cabral J. S (2010) Estatística, Mc-Graw-Hill de Portugal, 2ª ed. - Reis E., Melo P., Andrade R. e Calapez, T. (2007) Estatística Aplicada, Edições Silabo. - Montgomery, D. (1998) Applied Statistics and Probability for Engineers, , Wiley, 2nd ed. - Hayter, A. (2001), Probability and Statistics for Engineers and Scientists, Duxbury Press, 2nd ed. - Box, Hunter & Hunter (2005) Statistics for Experimenters, 2 ed. - Walpole, Myers and Myers (2011) Probability and Statistics for Engineers and Scientists, Prentice Hall, 9th ed. - Anselin, L. (1998) Spatial Eonometrics: Methods and Models. Kluwer Acad. Publishers. - Arbia, G. (2006) Spatial Econometrics - Statistical Foundations and Applications to Regional Convergence. - Fischer,M., Hewings,G., Nijkamp,P., Snickars,F., Nagurney,A. (2004) Advances in Spatial Science, Springer-Verlag. - Bailey, T. & Gatrell, A., Longman (1995) Interactive spatial data analysis.
Lectures with the help of audiovisual media where concepts, principles and theories are presented in detail. Practical exercises that meet all the needs of students are solved, with guidelines provided. In the remaining contact hours is provided support to solve the practical assignments that are considered for evaluation.