ISLA Santarém 194

Statistics

• ApresentaçãoPresentation

     
• ProgramaProgramme

  1. Descriptive statistics: Basic concepts: population, attribute, modalities and sample. Statistical data measurement scales. Absolute and relative frequencies. Accumulated frequencies. Measures of central tendency. Dispersion measures. Measures of skewness and kurtosis. 2. Probability theory: Basic concepts. Axioms of probabilities. Conditional probabilities. Independent events. Multiplicative and additive rules. 3. Random Variables: Discrete random variables: probability function, distribution function. Absolutely continuous random variables: probability density function, distribution function. Mathematical hope. Variance and standard deviation. Independent random variables. 4. Probability distributions: Discrete distributions. Continuous distributions.
• ObjectivosObjectives

  O1. Provide students with the knowledge that allows them to analyze data applying descriptive statistics methodologies. O2. Present the fundamental concepts of probability theory. O3. Provide students with knowledge of the language of probability and statistics. Competences: C1. Read and correctly interpret documents that make use of basic statistical language. C2. Formulate practical problems and express practical situations using the language of probability theory and statistics. C3. Read and correctly interpret documents that use probabilistic and statistical language. C4. Formulate practical problems and express practical situations using the language of probability theory and statistics. C5. Use SPSS software and interpret the outputs resulting from the application of descriptive statistics methods.
• BibliografiaBibliography

  Marôco, João (2018). Análise Estatística com SPSS, ReportNumber. Schiefer, H., & Schiefer, F. (2021). Statistics for Engineers: An Introduction with Examples from Practice. Springer Nature. Devore, J. L., Berk, K. N., & Carlton, M. A. (2021). Modern mathematical statistics with applications. 3rd edition. New York: Springer. Rhinehart, R. R., & Bethea, R. M. (2022). Applied Engineering Statistics. CRC Press. Gupta, B. C., Guttman, I., & Jayalath, K. P. (2020). Statistics and probability with applications for engineers and scientists. Wiley.
• MetodologiaMethodology

  Synchronous distance learning: 1. Expository methodology: Presentation of concepts and tools. 2. Active methodologies: Presentation, discussion and interpretation of statements. Face to face: 3. Practice: solving exercises by students with collective and individual discussion of the issues that the problem raises in its resolution. Autonomous: 4. Study and solve additional exercises/problems proposed by the teacher. The teacher provides feedback (Tutorial Guidance - OT) on the results obtained by the student in solving the proposed exercises, in person in a classroom context or remotely in asynchronous mode via the Moodle platform.
• LínguaLanguage

  Português
• TipoType

  Semestral
• ECTS

  5
• NaturezaNature

  Mandatory
• EstágioInternship

  Não
• AvaliaçãoEvaluation

  Avaliação Curricular (contínua):
  A1. Portfólio de exercícios resolvidos em aula.
  A2. Teste intermédio - individual.
  A3. Teste intermédio - individual.
  A classificação final é calculada através da fórmula Classificação Final = A1*0,2+ A2*0,4+A3*0,4.
  O estudante é aprovado se obtiver classificação igual ou superior a 9,5 valores.
  Avaliação Final (A): O estudante realiza o exame teórico-prático  (A=100%) e é aprovado se obtiver uma classificação igual ou superior a
  9,5 valores em 20.
  Avaliação em Época de Recurso e Época Especial (A): O estudante realiza o exame teórico-prático  (A=100%) e fica aprovado se obtiver
  uma classificação igual ou superior a 9,5 valores em 20.