ISLA IPGT 26070

Data Analysis Tools

• ApresentaçãoPresentation

  The ?Data Analysis Tools? course aims to provide students with fundamental skills in manipulating, exploring and interpreting data, combining knowledge of descriptive statistics and digital tools, with a special focus on Microsoft Excel. Field of Action and Area of Expertise This course is in the area of data analysis and processing, with applications in various fields such as management, economics, engineering, social sciences and health. The knowledge acquired will be essential for data-based decision-making and for solving quantitative problems in different professional contexts. Intervention Areas Students will learn to: Apply descriptive statistics to analyse data; Use Excel to process and visualise information; Create basic regression models and interpret results; Build dynamic tables and dashboards for decision support.
• ProgramaProgramme

  1. descriptive statistics easures of central tendency and dispersion (mean, median, mode, variance, standard deviation) Graphical representation of data (histograms, boxplots, scatter plots) Simple linear regression and interpretation of results Confidence intervals in data analysis 2. Microsoft Excel - Tools for analysing data Basic functions and statistics in Excel Filters, sorting and use of PROC-V, PROC-X, INDEX, CORRESP Building personalised graphs 3. Pivot Tables and Dashboards Creating and manipulating pivot tables Data segmentation and personalised calculations Building interactive dashboards
• ObjectivosObjectives

  Knowledge Students should: Understand the fundamental concepts of descriptive statistics (measures of central tendency, dispersion and data distribution); Know the principles of linear regression and confidence intervals; Master the main features of Excel for analysing and visualising data; Understand the importance of organising and structuring data to support decision-making. Skills Students will be able to: Apply statistical techniques to explore and summarise data; Use formulas and functions in Excel to process and analyse data; Build dynamic tables to organise information efficiently; Create interactive dashboards for the visual presentation of relevant data. Competences On completion of the course, students should be able to: Interpret and communicate statistical results clearly and objectively; Use digital tools to support data-based decision-making;
• BibliografiaBibliography

  Levine, D. M., Stephan, D. F., & Szabat, K. A. (2017). Estatística: Teoria e Aplicações Usando o Microsoft Excel em Português (7ª ed.). São Paulo: Pearson Education do Brasil. 784 páginas. ISBN 978-85-221-2765-0. Spiegelhalter, D. (2019). A Arte da Estatística: Como Aprender com Dados . Lisboa: Temas e Debates. 448 páginas. ISBN 978-989-644-587-3. Wheelan, C. (2017). Estatística: O que é, para que serve, como funciona . Rio de Janeiro: Zahar. 320 páginas. ISBN 978-85-378-1032-8. Walkenbach, J. (2018). Excel 2019 Bible . Indianapolis: Wiley. 1120 páginas. ISBN 978-1-119-51479-2. Jelen, B., & Alexander, M. (2018). Microsoft Excel 2019: Data Analysis and Business Modeling (6ª ed.). Redmond: Microsoft Press. 624 páginas. ISBN 978-1-5093-0616-9.  
• MetodologiaMethodology

  1. Use of Infographics and Visual Resources Use of explanatory infographics to illustrate statistical concepts and Excel functionalities. Visual representation of processes, such as flowcharts for creating dashboards and pivot tables. 2. Practical Teaching with Digital Tools Real-time demonstrations in Excel, guided by the lecturer, to apply the concepts. Use of real datasets for data analysis and interpretation exercises. 3. Personalised Feedback and Ongoing Support Follow-up sessions to clarify doubts and reinforce content. Continuous feedback on student progress, with suggestions for improvement.
• LínguaLanguage

  Português
• TipoType

  Semestral
• ECTS

  6
• NaturezaNature

  Mandatory
• EstágioInternship

  Não