ISLA Santarém 194

Statistics

• ApresentaçãoPresentation

  The Statistics course aims to introduce the fundamental principles of data analysis and probability theory, providing a solid foundation for the application of statistical methods in different areas of study. This discipline is essential for understanding and interpreting data, aiding in making informed decisions based on quantitative evidence. Statistical knowledge is crucial in many areas where data analysis plays an increasingly relevant role, particularly, in the areas of social sciences, economics, engineering, health sciences and technology, as is the case of the Bachelor Degree in Business Process and Operations Management. The course encourages students' critical and analytical thinking with practical applications in order to contribute positively to their academic and professional future.
• ProgramaProgramme

  1. Descriptive statistics 1.1. Basic concepts: population, statistical unit, attribute, and sample 1.2. Measurement scales of statistical data 1.3. Absolute and relative frequencies 1.4. Cumulative frequencies 1.5. Measures of location 1.6. Measures of dispersion: variance and standard deviation 1.7. Measures of skewness and kurtosis 2. Probability theory 2.1. Basic concepts 2.2. Axioms of probability 2.3. Conditional probabilities 2.4. Independent events 2.5. Multiplicative and additive rules 3. Random Variables 3.1. Discrete random variables: probability function, distribution function 3.2. Absolutely continuous random variables: probability density function, distribution function 3.3. Random Variable Parameters: expected value, variance and standard deviation 3.5. Independent random variables 4. Probability Distributions 4.1. Discrete distributions 4.2. Continuous distributions
• ObjectivosObjectives

  The objectives of the curricular unit are: O1. To present the main concepts of descriptive statistics, probability and statistical functions; O2. Make known probability computation methods and their practical application in decision making; O3. Summarize and interpret univariate and bivariate data using software of statistical analysis; O4. Read and correctly interpret documents that make use of basic probabilistic and statistical language; O5. Formulate practical problems and express practical situations using the language of probability theory and statistics. At the end of the curricular unit students should be able to: C1. Analyze data by applying methods of descriptive statistics using software of statistical analysis; C2. Express situations of uncertainty relevant to decision making using probabilistic and statistical language; C3. Use statistical analysis software, such as SPSS and R Commander, and interpret the outputs resulting from the application of descriptive statistical methods.
• BibliografiaBibliography

  Doane, D., Seward, L. (2014) Estatística Aplicada à Administração e à Economia. 4.ª Edição, AMGH Editora, Ltda. Fidell, L., Tabachnick, B. (2019). Using Multivariate Statistics. 7th Edition, Pearson. Maroco, J. (2021). Análise Estatística com o SPSS Statistics. 8.ª Edição, ReportNumber. Reis, E. (2018). Estatística Descritiva. 7.ª Edição revista e corrigida, Edições Síbabo. Reis, E. et al. (2015). Estatística Aplicada 1. Volume 1, 6.ª Edição revista e aumentada, Edições Sílabo. Robalo, A. (2017). Estatística: Exercícios, Volume I - Probabilidades e variáveis aleatórias. 6.ª Edição, Edições Sílabo.  
• MetodologiaMethodology

  The classes will address the concepts of the different themes and, later, show their practical application, with a series of exercises inside and outside the classroom, inducing the active and autonomous participation of students.   For this purpose, the use of the expository method is foreseen to introduce the concepts and structure the reasoning and the interrogative method for the learning evaluation, in the theoretical aspect of each chapter. With regard to the practical aspect, the use of the demonstrative method is foreseen for the practical illustration of the contents, as well as active, participatory and autonomous methods to make the connection with the experience of each one.   In summary: (1) Expository and Interrogative Methodology - participatory teaching, resorting whenever necessary to Motivation strategies and to (2) Active Pedagogical Methodologies such as Flipped Classroom, Gamification and Problem/Project Based Learning.
• LínguaLanguage

  Português
• TipoType

  Semestral
• ECTS

  6
• NaturezaNature

  Mandatory
• EstágioInternship

  Não
• AvaliaçãoEvaluation

  Época Normal - Avaliação curricular (contínua) (*): O estudante constrói um portfólio com base nas atividades de avaliação ativa desenvolvidas ao longo do semestre e realiza dois testes de avaliação individual. 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 = 0.3*P+0.35*T1+0.35*T2, onde P, T1 e T2 denotam, respetivamente, as notas no portfólio e nos testes de avaliação 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	Ponderação
  Portfólio	Consultar Moodle, consoante a turma.	30%
  Teste 1	13-11-2025	35%
  Teste 2	08-01-2026	35%
  Exames	A agendar pelos serviços.	100%