ISLA Santarém 979

Statistics I

• ApresentaçãoPresentation

  The course introduces the fundamental principles of probability and data analysis, developing skills to describe, interpret, and model quantitative information and support evidence-based decisions, with applications in occupational safety engineering and other scientific and technological areas.
• 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

  Marôco, João (2021). 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

  The methodology used in classes will strike a balance between theoretical foundations and their practical application. Classes will address different topics and then demonstrate their practical application through a series of exercises inside and outside the classroom, encouraging active and independent participation by students.  To this end, the expository method will be used to introduce concepts and structure reasoning, and the interrogative method will be used to assess learning in the theoretical part of each chapter. In the practical part, the demonstrative method will be used to provide practical examples of the content, as well as active, participatory, and autonomous methods to connect with each student's experience. Summary: Expository and Interrogative Methodology – participatory teaching, using motivational strategies and active pedagogical methodologies such as flipped classrooms, gamification, and problem/project-based learning whenever necessary.
• LínguaLanguage

  Português
• TipoType

  Semestral
• ECTS

  6
• NaturezaNature

  Mandatory
• EstágioInternship

  Não
• AvaliaçãoEvaluation

  Avaliação Curricular (*): O estudante realiza 2 fichas de exercícios em grupo e dois testes individuais. O estudante aprova se a classificação final for superior ou igual a 9.5 valores. A classificação final é calculada pela fórmula Classificação Final = 0.2*F1+0.3*T1+0.2*F2+0.3*T2, onde F1, F2, T1 e T2 denotam, respetivamente, as notas nas fichas de exercícios e nos testes individuais. 
  Avaliação Final: O estudante realiza o exame completo e aprova se obtiver classificação superior ou igual a 9.5 valores.
  Época de Recurso e Época Especial: O estudante realiza o exame completo e aprova se obtiver classificação superior ou igual a 9.5 valores.