Statistics II
Objectives
This curricular unit aims to extend the knowledge acquired in Statistics I, as well as supplying to the students theoretical and practical knowledge about more advanced methodologies on parametric inference. The contents of the curricular unit include inference tools such as statistics, estimators, sampling distributions, point and interval estimation and hypothesis testing. Additionally, some issues of asymptotic distributions are addressed. The students will acquire competences related to the point estimators and their properties, and will learn how to construct confidence intervals and perform hypothesis testing on population parameters, such as the mean, the variance, the difference between means, the ratio of variances, the proportion, the difference between proportions and the correlation coefficient. Moreover, the analysis of variance is introduced. The students should clearly understand the conditions of applicability of each procedure.
General characterization
Code
100055
Credits
6.0
Responsible teacher
Ana Cristina Marinho da Costa
Hours
Weekly - Available soon
Total - Available soon
Teaching language
Portuguese. If there are Erasmus students, classes will be taught in English
Prerequisites
In order to meet the leaning objectives successfully, students must possess knowledge of Statistics I, Math I and Math II.
Bibliography
Afonso, A., Nunes, C. (2011). Estatística e Probabilidades. Aplicações e Soluções em SPSS, Escolar Editora.
Carvalho, A. (2015). Exercícios de Excel para Estatística. FCA - Editora de Informática.
Hogg, R. V., Tanis, E. A. (2010). Probability and Statistical Inference. 8th Edition, New Jersey: Pearson/Prentice-Hall.
Newbold, P., Carlson, W. L., Thorne, B. (2012). Statistics for Business and Economics. 8th Edition, Boston: Pearson.
Murteira, B., Ribeiro, C.S., Silva, J.A. e Pimenta, C. (2002). Introdução à Estatística. McGraw Hill.
Pedrosa, A. C. e Gama, S. M. A. (2004). Introdução Computacional à Probabilidade e Estatística. Porto Editora, 2004.
Teaching method
The curricular unit is based on theoretical-practical classes and practical classes. The practical part of the course is aimed at solving problems and completing exercises. It is also proposed an exercise book that should be solved with individual work in the tutorial sessions of some practical classes and out of classes.
Evaluation method
1st call: three in-class tests (1/3 weight each), and it is required a minimum score of 9 points in two of the tests (0-20 scale).
2nd call: final exam (100%).
Subject matter
The curricular unit is organized in five Learning Units (LU):
LU1: Sampling distributions: concepts; Central Limit Theorem; distribution of the sampling mean, difference between means, variance, ration between variances, proportion, difference between proportions
LU2: Point estimation: the method of maximum likelihood; properties of the estimators
LU3: Interval estimation: confidence intervals for the mean, difference between means, variance, ratio between variances, proportion, difference between proportions
LU4: Hypothesis testing: concepts and methodology; hypothesis testing for the mean, difference between means, variance, ratio between variances, proportion, difference between proportions, correlation coefficient
LU5: Analysis of variance (ANOVA): analysis of variance with one factor and fixed effects; multiple comparison tests
Programs
Programs where the course is taught: