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Statistical Methods

Code:

LTAM35

Sigla:

ME

Áreas Científicas
Classificação	Área Científica
OFICIAL	Matemática

Ocorrência: 2023/2024 - 2S

Ativa?	Yes
Página Web:	https://moodle.ips.pt/2324/course/view.php?id=2387
Unidade Responsável:	Departamento de Matemática
Curso/CE Responsável:	Environmental and Marine Technology

Ciclos de Estudo/Cursos

Sigla	Nº de Estudantes	Plano de Estudos	Anos Curriculares	Créditos UCN	Créditos ECTS	Horas de Contacto	Horas Totais
LTAM	74	Plano de Estudos 2016/17	2	-	6	67,5	162

Língua de trabalho

Portuguese

Objetivos

The curricular unit contents are structured, regarding its suitability for the intended learning outcomes.
Therefore, each subject approaches fundamental theoretical concepts and practical applications by solving problems using the basic tools of Probability and Statistics to enable students to analyze certain phenomena of random nature, framed in the context technology.

Resultados de aprendizagem e competências

1) Describe and apply techniques for summarizing a data set.
2) Solve problems involving models and probability distributions with discrete variables and with continuous variables
3) Characterize and apply estimators.
4) Construct and interpret confidence intervals.
5) Identify and apply the appropriate parametric hypotheses test.
6) Identify and apply the appropriate nonparametric hypotheses test.
7) Build and analyze a simple linear regression model.

Modo de trabalho

Presencial

Pré-requisitos (conhecimentos prévios) e co-requisitos (conhecimentos simultâneos)

Basic knowledge of Mathematics.

Programa

DESCRIPTIVE STATISTICS
Describe and apply techniques for summarizing a data set.
THEORETICAL DISTRIBUTIONS
Discrete and continuous probability distributions
ELEMENTS OF SAMPLING THEORY
Random sample, independent samples and paired samples. Some Sampling Distributions
ELEMENTS OF ESTIMATION THEORY
Point and interval estimates. Confidence Intervals for mean, for proportion and for variance. Confidence Intervals for the difference between two means, for the difference between two proportions and for the ratio of two variances.
PARAMETRIC HYPOTHESIS TESTING (HT)
HT for mean, for proportion and for variance. HT for the difference between two means, for the difference between two proportions and for the ratio of two variances.
NONPARAMETRIC HYPOTHESIS TESTING
Tests of goodness of fit. ChiSquare Independence test. Wilcoxon test. Mann-Whitney test
SIMPLE LINEAR REGRESSION
Build and analyze a simple linear regression model.

Bibliografia Obrigatória

Montgomery, D.; Runger, G.; Applied Statistics and Probability for Engineers, 5th ed., John Wiley & Sons, 2011
Murteira, B.; Antunes, M.; Probabilidades e Estatística, Volumes 1 e 2, Escolar Editora, 2012
Murteira, B.; Ribeiro, C. S.; Andrade e Silva, J.; Pimenta, C.; Introdução à Estatística, 2ª edição, McGraw-Hill, 2008

Bibliografia Complementar

André, J.; Probabilidades e Estatística para Engenharia, Lidel
Galvão de Melo, F.; Probabilidades e Estatística: conceitos e métodos fundamentais, Volumes 1 e 2, Escolar Editora
Graça, M. E.; Introdução às Probabilidades e Estatística, DEIO, FCUL, Sociedade Portuguesa de Estatística
Murteira, B; Análise Exploratória de Dados: Estatística Descritiva, McGraw-Hill

Métodos de ensino e atividades de aprendizagem

Theoretical Practical classes: Theoretical exposure of the subjects followed by problems solving.
Laboratory Practical classes: Resolution of exercises using software R.

Software

Software R

Tipo de avaliação

Distributed evaluation with final exam

Componentes de Avaliação

Designation	Peso (%)
Teste	85,00
Trabalho escrito	15,00
Total:	100,00

Componentes de Ocupação

Designation	Tempo (Horas)
Estudo autónomo	94,50
Frequência das aulas	45,00
Trabalho laboratorial	22,50
Total:	162,00

Obtenção de frequência

The approval in this curricular unit can be obtained through two assessment processes: Continuous Evaluation or Exam Evaluation.

Continuous Evaluation 
2 tests and 1 practical work developed in group.

Exam Evaluation
Evaluation by final examination.

Fórmula de cálculo da classificação final

Continuous Evaluation 

Assigning by T1 the classification of the first test, T2 the classification of the second test and by Trab the classification of the practical work, the final classification (CF) is:

CF = 0.5×T1+0.35×T2+0.15×Trab

• If CF is greater than or equal to 10 and less than 18, the student is approved with a final grade equal to CF, provided that the classification in any of the tests was greater or equal to 7.0 values.

• If the CF is equal or greater than 18, the student must do an oral exam. The final grade is the average between the tests and the grade of the oral exam. If the student does not attend the oral exam, the final classification will be 17.

• If CF is less than 10, students will be able to recover the lowest test by performing a recovery test (in the same day of the first exam), provided that one of the tests is greater or equal to 7.0 values.

Exam Evaluation

• If the grade of the exam is greater or equal to 10 and less than 18, the student is approved with a final mark equal to the grade of the exam.

• If the grade of the exam is equal or greater than 18, the student must do an oral exam. The final grade is the average between the two grades. If the student does not attend the oral exam, the final classification will be 17 points.

Observações