Estatística e Gestão de Dados Urbanos

The following teaching methods will be used in the classes: expository with discussion; problem solving under the guidance of the teacher;
inverted classroom. Some of the problems will allow the use of common computational tools in data analysis. All the elements of the
syllabus will be covered within the framework of a case study on urban data that will be developed throughout the semester.

Understand the management and governance processes of urban management platforms.
Understand the different types of data, descriptive methods and statistical inference.
Understand methodologies and processes for analyzing and processing data.
Know how to use data analysis software.

1.Urban management platforms
Case studies.
Considerations on platform architecture and data governance.
2.Descriptive Statistics
Urban data sources: sensors, images, administrative data.
Frequency distribution: tables and graphical representation.
Summary measures of a variable.
Measures of association between two variables.
3.Main probability distributions
Probability topics.
Concept of random variable.
Discrete distributions: binomial and Poisson.
Continuous distributions: uniform, normal and exponential.
4.Notions of statistical inference
Confidence intervals for the mean, proportion and variance.
Hypothesis tests for mean, proportion and variance.
5.Data analysis process and CRISP-DM methodology
Application to case studies.

NAO