Currículo
Statistical Methods and Visualization SMV-DAB
Contextos
Groupo: Economia > 2º Ciclo > Parte Escolar > Unidades Curriculares Optativas > Optativa Condicionada 3 e 4
ECTS
6.0 (para cálculo da média)
Objectivos
By the end of this course, students should be able to manipulate and visualize data using the R language for statistical computing and graphics. They should also learn how to build and interpret simple regression models.
Programa
Introduction to the R language for statistical computing and graphics. The linear regression model. The logistic regression model. Fundamentals of data visualization.
Método de Avaliação
The teaching methodology encompasses both theoretical and practical aspects. In class, theoretical concepts are introduced alongside illustrative problems, which are presented and solved using the R language for statistical computing. Regular homework is also given, aimed at consolidating the in-class material. The final exam consists of 2 hours and it is split into two parts: the first part is a closed-book written exam (only pen and paper), and the second part is in the software R on the ISEG desktop computers from the exam room. Personal laptops, tablets, phones or other devices are not allowed. Each 1h part part of the exam represents 50% of the final mark.
Carga Horária
Carga Horária de Contacto -
Trabalho Autónomo - 129.0
Carga Total -
Bibliografia
Principal
- An Introduction to Statistical Learning with Applications in R: Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani 2021 Springer
- A Modern Approach to Regression with R: Simon Sheather 2009 Springer
- The Art of R Programming: A Tour of Statistical Software Design: Norman Matloff 2011 No starch press
- Fundamentals of Data Visualization: Claus O. Wilke 2019 O'Reilly
- ggplot2: Elegant Graphics for Data Analysis: Hadley Wickham 2016 Springer