Urban Data Analysis

Recommended Prerequisites

Não há requisitos específicos além das condições gerais de admissão ao ciclo de estudos.

Teaching Methods

Each class will have a brief presentation of the subject followed by practical exercises in a computer environment related to the final objective, with students being asked to present results throughout the class.

Learning Outcomes

To provide students with the knowledge that will enable them to develop statistical analyses of territory and transport databases.
Skills to be developed:
Ability to develop various analyses of urban data using programs such as Excel, ArcGisPro, SPSS and Rstudio.

Work Placement(s)

No

Syllabus

• Introduction - General
• Multiple Linear Regression - Demand studies
• Principal Components Analysis and Factor Analysis
• Cluster Analysis and Analysis of Variance
• Generalized Linear Models
• Panel Data Models / Territorial Regression Models

Head Lecturer(s)

Anabela Salgueiro Narciso Ribeiro

Assessment Methods

Assessment
Exam: 40.0%
Synthesis work: 60.0%

Bibliography

[1] Washighton, C. et al (2003) Statistical and econometric methods for transportation data analysis
[2] Lovelace, R. et al (2019) Geocomputation with R.
[3] Oyana, Tonny J. (2015) Statistics, Visualization and Computational Methods – From Data to Information
[4] Pebesma, Edzer & Bivand, Roger (2023) Spatial Data Science with applications in R