Base Knowledge
Knowledge of high-school Mathematics.
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 or R or Python and manipulate and analyze data.
Learning Results
The goals of this course are:
a) Deepen the knowledge of Descriptive Statistics developed during Secondary Education;
b) Learn techniques of Inferential Statistics and its assumptions in order to use them wisely and critically,
acknowledge their limitations, and interpret correctly the results;
c) Use software to describe data and to apply the techniques of statistical decision and correctly interpret the
results.
Program
1. Descriptive Statistics
– Data organization
– Frequency tables and graphical representation
– Measures of location and dispersion
– Contingency tables and scatter plots
2. Statistical Inference
– Probability
– Random variable
– Discrete distributions: binomial, hypergeometric, and Poisson
– Continuous distributions: uniform, normal, and exponential
– Confidence intervals and hypothesis testing
3. Introduction to Regression
4. Introduction to Multivariate Statistics: dimensionality reduction and classification
Curricular Unit Teachers
Internship(s)
NAO
Bibliography
Recommended (available for free online)
Professor’s notes, available in Moodle.
Several authors (2020), ALEA – Ação Local Estatística Aplicada, Instituto Nacional de Estatística, http://www.alea.pt
Complementary
Pedrosa, A. e Gama, S. (2018) – Introdução Computacional à Probabilidade e Estatística com Excel, Porto Editora
Reis, E., Melo, P., Andrade, R. e Calapez, T. – Estatística Aplicada – Vols. 1 e 2, Edições Sílabo
Reis, E., Melo, P., Andrade, R. e Calapez, T. – Exercícios de Estatística Aplicada – Vols. 1 e 2, Edições Sílabo
Ross, Sheldon (2014) – Introduction to Probability and Statistics for Engineers and Scientists, Elsevier
Ryan, T. (2007) – Modern Engineering Statistics, Wiley
R Core Team (2022)- An Introduction to R – Notes on R: A Programming Environment for Data Analysis and
Graphics, https://cran.r-project.org/doc/manuals/R-intro.pdf, Version 4.2.1, 23/06/2022
Shaw, Z. (2017) – Learn Python 3 the Hard Way, Addison-Wesley Professional.