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ISMAT 620

Probabilities and Statistics

IT Engineering
  • ApresentaçãoPresentation
    The value of data is now recognized in numerous application areas and organizations are increasingly using it to support decision making.  This Curricular Unit starts by introducing the introductory concepts of Statistics, followed by the presentation of various types of tables, graphs and descriptive measures that can be used to organize and characterize the data.  Then the concept of probability is introduced, various probability distributions are studied and we proceed to Inferential Statistics, which aims to infer about the population, based on the knowledge of the sample data, including the point and interval estimation of parameters and testing hypotheses about these.  The correlation between quantitative variables is also analyzed graphically and analytically and simple and multiple linear regression models are developed, which are very useful for predictive purposes.  The softwares jamovi and R: A language and environment for statistical computing, will be used. 
  • ProgramaProgramme
    S1: Introduction to Statistics  The power of data  Data Science  Basic concepts of Statistics  Statistical method steps   S2: Descriptive Statistics  Descriptive measures  Tables and graphical representations   S3: Probabilities  Introduction to probabilities  Conditional probability and Bayes' theorem   S4: Random Variables and Discrete Distributions Discrete random variables  Binomial distribution  Poisson distribution   S5: Random Variables and Continuous Distributions Continuous random variables  Normal distribution   S6: Inferential Statistics  Introduction to Inferential Statistics  Point and interval estimation  Parametric and nonparametric hypothesis tests Hypothesis tests to compare population means Chi-square independence test   S7: Correlation and Linear Regression  Linear correlation  Simple linear regression  Multiple linear regression   S8: Data Analysis using Softwares R and jamovi 
  • ObjectivosObjectives
    At the end of this course unit, students should be able to:  LO1: Distinguish fundamental concepts of Statistics;  LO2: Represent data through tables, graphs and descriptive measures; LO3: Solve problems involving probabilities and random variables;  LO4: Perform confidence intervals and hypothesis testing;  LO5: Analyze correlations and fit linear regression models to data;  LO6: Use softwares jamovi and R for statistical data analysis.
  • BibliografiaBibliography
    Maindonald, J. & Braun, W. J. (2010). Data analysis and graphics using R: an example-based approach. (3rd ed.). United Kingdom: Cambridge University Press.  Murteira, B. & Antunes, M. (2012). Probabilidades e Estatística . (Vol. 1). Lisboa: Escolar Editora.   Paulino, C. & Branco, J. (2005). Exercícios de Probabilidade e Estatística . Lisboa: Escolar Editora.
  • MetodologiaMethodology
    Active, problem-solving-oriented methodologies (PBL) are used for all content.
  • LínguaLanguage
    Português
  • TipoType
    Semestral
  • ECTS
    6
  • NaturezaNature
    Mandatory
  • EstágioInternship
    Não