Base Knowledge
Knowledge of Mathematics, Probability and Statistics at a non higher education level.
Teaching Methodologies
In the theoretical classes will be used the expository method with discussion. The practical classes will be dedicated to problem solving under the guidance of the teacher. Some of the issues to address will allow students to use Excel and manipulate and analyze data.
Learning Results
Provide the fundamentals of Statistics and Probability necessary for the study and understanding of phenomena of interest in your area of training. Learn the main concepts and methods of interpretation and data processing. To know the probabilistic models that constitute the basis of statistical inference. Learn how to use and interpret basic tools of statistical inference. Use of Excel.
Program
1. Descriptive statistics.
Descriptive Statistics’ objectives. Population and sample. Data types and measure scales. One dimension Descriptive statistics. Organization of data in frequency tables and graphical representation. Location measures and dispersion measures. Descriptive statistics in two dimensions. Contingency tables. Location and scatter measures for two-dimensional data. Covariance and correlation coefficient. Linear regression. Regression line. Coefficient of determination. Problem solving with Excel.
2. Introduction to probability theory.
Review of basic concepts: random experience, sample space, event. Probability of an event (definition and properties). Conditional probability and composite probability. Independence of events. Distributions: binomial and normal. Central Limit Theorem: fundamentals/simulation. Problem solving with Excel.
3. Introduction to Statistical Inference.
Brief introduction to sample design. Random sample. Sampling distributions. Point estimation and interval estimation. Confidence interval for mean values, proportions and variances in normal populations. Introduction to hypothesis tests for mean, standard deviation and proportion. Applications. Problem solving with Excel.
Curricular Unit Teachers
Internship(s)
NAO
Bibliography
Recommended (available for free online)
Apontamentos das aulas, disponibilizados pelo docente no Moodle.
Vários (2020), ALEA – Ação Local Estatística Aplicada, Instituto Nacional de Estatística, http://www.alea.pt
Complementary
F. Araújo Canova (2013), Apontamentos das aulas teóricas e caderno de exercícios das aulas teórico práticas.
Pedrosa, A. e Gama, S. (2018) – Introdução Computacional à Probabilidade e Estatística com Excel, Porto Editora
Guimarães, R.C. e Cabral J., Estatística (2009), 2.ª edição – Mc Graw Hill
Murteira, B. J., Ribeiro, C. S., Andrade e Silva, J. e Pimenta, (2002) – Introdução à Estatística, McGraw Hill
Reis, Elizabeth et all (1997), Estatística Aplicada, Vol I e Vol II, Edições Sílabo
Robalo, A. (1991), Estatística – Exercícios, Vol I e II, Edições Sílabo