ISLA Santarém 17676

Data Processing and Analysis

• ApresentaçãoPresentation

  The Data Processing and Analysis course aims to introduce and deepen the fundamental principles of data analysis and statistics, providing a solid basis for the application of statistical methods in different areas of study. This discipline is essential for understanding and interpreting data, helping to make informed decisions based on quantitative evidence. Statistical knowledge is crucial in many areas where data analysis plays an increasingly relevant role, in particular in the areas of social sciences, economics and management, as is the case with the Master's in Business Management. The student's critical and analytical thinking is encouraged with practical applications in order to contribute positively to their academic and professional future.
• ProgramaProgramme

  1. Data collection methods and techniques 1.1 Steps of a survey 1.2 Types of research 1.3 Data Sources 1.4 Qualitative and quantitative methods of data collection 1.5 The sampling process. Sample size. 2. Construction of questionnaires 2.1 Process of preparing questionnaires 2.2 Questionnaire Methods 2.3 Types of questions 2.4 Measures and scales 3. Data entry in SPSS 3.1 Overview 3.2 Introduction of variables and cases 3.3 Insertion of new variables and cases 3.4 Variable Transformation 3.5 SPSS Applications 4. Data treatment: application and interpretation of statistical methods 4.1 Univariate and bivariate analysis 4.2 Linear regression analysis 4.3 Factor analysis 4.4 Cluster analysis
• ObjectivosObjectives

  The objectives of the course are: O1. Present methods for collecting, analyzing and processing quantitative and qualitative data/information; O2. Understand the rules for building a questionnaire, the types of measures and scales; O3. Use appropriate statistical methods in data processing using statistical analysis software; O4. Develop logical, critical and analytical reasoning in a creative way. At the end of the course, students should be able to: C1. Analyze data and interpret the results of applying statistical methods using statistical analysis software; C2. Interpret, formalize and solve relevant problems in organizational terms based on statistical instruments and tools and on data analysis. C3. Use the SPSS statistical analysis software, and interpret the outputs resulting from the application of appropriate statistical methods.
• BibliografiaBibliography

  Botelho, M., & Laureano, R. (2017). SPSS Statistics – O meu manual de consulta rápida. 3.ª Edição, Edições Sílabo. Fidell, L., & Tabachnick, B. (2019). Using Multivariate Statistics. 7th Edition, Pearson. Frankfort-Nachmias, C., & Leon-Guerrero, A. (2018). Social Statistics for a Diverse Society. 8th Edition, SAGE Publications. Malhotra N. (2019). Marketing Research: An Applied Orientation. 7th Edition, Pearson. Marôco, J. (2021). Análise Estatística com o SPSS Statistics. 8.ª Edição, ReportNumber. Pestana, M., & Gageiro, J. (2014). Análise de Dados para Ciências Sociais - A Complementaridade do SPSS. 6.ª Edição, Edições Sílabo. Pinto, R. (2022). Introdução à Análise de Dados: Com recurso ao SPSS. 3.ª Edição, Edições Sílabo.
• MetodologiaMethodology

  1. For this purpose, it is planned to use the expository method to introduce the concepts and structure the reasoning and the interrogative method for the evaluation of learning, in the theoretical aspect of each chapter. 2. With regard to the practical aspect, it is planned to use the demonstrative method for the practical exemplification of the contents and also active, participatory and autonomous methods to make the connection with the experience of each one. 3. Consolidation of the contents taught in class through the search for additional information on the different topics covered and the development of additional work. In summary: Expository and Interrogative Methodology - participatory teaching, resorting whenever necessary to Motivation strategies and Active Pedagogical Methodologies such as Flipped Classroom, Gamification, Classroom-Based Learning, Problems/Projects and Team-Based Learning.
• LínguaLanguage

  Português
• TipoType

  Semestral
• ECTS

  6
• NaturezaNature

  Mandatory
• EstágioInternship

  Não
• AvaliaçãoEvaluation

  Época Normal - Avaliação curricular (contínua) (*): O estudante constrói um portfólio formado por três atividades de avaliação ativa desenvolvidas ao longo do semestre. O estudante aprova se a classificação final for superior ou igual a 9.5 valores em 20 valores. A classificação final é calculada pela fórmula Classificação Final = 0.45*P1+0.45*P2+0.1*P3, onde P1, P2 e P3 denotam, respetivamente, as notas nas atividades do portfólio. A atividade 1 do portfólio (P1) e a atividade 2 do portfólio (P2) são realizadas em grupo. A atividade 3 do portfólio (P3) é realizada de forma individual.

  (*) A realizar no decorrer do semestre.

  Época Normal - Avaliação final: O estudante realiza o exame completo e aprova se obtiver classificação superior ou igual a 9.5 valores em 20 valores.

  Épocas de Recurso e Especial: O estudante realiza o exame completo e aprova se obtiver classificação superior ou igual a 9.5 valores em 20 valores.

  Descrição	Data limite	Ponderação
  Atividade 1 do Portfólio (P1)	15-11-2025	45%
  Atividade 2 do Portfólio (P2)	29-11-2025	45%
  Atividade 3 do Portfólio (P3)	03-01-2026	10%
  Exames	A agendar pelos Serviços.	100%