ISMAT 1790

Exploratory Data Analysis

• ApresentaçãoPresentation

  Data science as a means of decision making. Quantitative and graphical techniques in data processing. Identify the structure of a data set regarding trends, outliers and patterns.
• ProgramaProgramme

  S1. Notions of data science and data mining S2. Identifying the structure of a data set S3. Properties of a dataset. S4. Quantitative and graphical tools applied to data processing.
• ObjectivosObjectives

  LG1 - Notions of data science. LG2 - Develop quantitative and graphical techniques in data processing. LG3 - Identify the structure of a data set regarding trends, outliers and patterns.
• BibliografiaBibliography

   Reis, E. (2008). Estatística Descritiva . Lisboa: Sílabo. Reis, E., P. Melo, R. Andrade & T. Calapez (2015). Estatística Aplicada (Vol. 1) . Lisboa: Sílabo Reis, E., P. Melo, R. Andrade & T. Calapez (2012). Exercícios de Estatística Aplicada (Vol. 1) Lisboa: Sílabo. Sicsú, A. & Dana, S. (2012). Estatística Aplicada . São Paulo: Editora Saraiva Sweeney, D. J., Williams, T. A., & Anderson, D. R. (2013). Estatística Aplicada à Administração e Economia . São Paulo: Cengage Learning
• MetodologiaMethodology

   ME1. Theoretical exposition of the main syllabus contents (CP); ME2. Exercise resolution. Assessment : - Group work (70%) - Work in the classroom (20%) - Attendance and active participation in classes (10%).
• LínguaLanguage

  Português
• TipoType

  Semestral
• ECTS

  3
• NaturezaNature

  Mandatory
• EstágioInternship

  Não