Esta página em português Ajuda Autenticar-se

Você está em: Start > TGI14

Campus Map

Options

Statistics

Code:

TGI14

Sigla:

Áreas Científicas
Classificação	Área Científica
OFICIAL	Matemática

Ocorrência: 2021/2022 - 2T

Ativa?	Yes
Página Web:	https://moodle.ips.pt/2122/course/view.php?id=251
Unidade Responsável:	Departamento de Matemática
Curso/CE Responsável:	Industrial Management and Techinology

Ciclos de Estudo/Cursos

Sigla	Nº de Estudantes	Plano de Estudos	Anos Curriculares	Créditos UCN	Créditos ECTS	Horas de Contacto	Horas Totais
TGI	74	Plano de Estudos 2016	2	-	4	44	108

Docência - Responsabilidades

Docente	Responsabilidade
Paula Cristina Sequeira Pereira

Docência - Horas

Theorethical and Practical :	2,00
E-Learning:	2,00

Type	Docente	Turmas	Horas
Theorethical and Practical	Totais	2	4,00
Theorethical and Practical	Paula Cristina Sequeira Pereira		4,00
E-Learning	Totais	1	2,00
E-Learning	Paula Cristina Sequeira Pereira		2,00

Língua de trabalho

Portuguese

Objetivos

The curricular unit contents are structured, regarding its suitability for the intended learning outcomes.

Therefore, each subject approaches fundamentals concepts and practical applications by solving problems using the basic tools of Statistics to enable students to analyze certain phenomena of random nature, framed in the context of technology.

Resultados de aprendizagem e competências

(a) Provide basic training about techniques and theory of statistical learning.

(b) Identify the main theoretical models studied.

(d) Build and interpret parametric hypothesis testing.

(e) Estimate and interpret the parameters of the linear regression model.

(f) Apply the techniques of statistical inference as decision-making support tool and nterpret the results.

(g) Review, evaluate, interpret and defend critical sense results obtained.

Modo de trabalho

B-learning

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

Basic knowledge of Mathematics.

Programa

1. Random Variables

Concept of random variable. Probability function and density probability function for discrete and continuous random variables, respectively. The Cumulative Distribution function. Location and dispersion parameters: expected value, variance and standard deviation, characterization and properties.

2. Theoretical Distributions

Discrete Distributions: Binomial Distribution and Poisson Distribution. Characterization, properties and parameters. Continuous Distributions: Exponential Distribution and Normal Distribution. Characterization, properties and parameters. A brief reference to the Student-t Distribution.

3. Elements of Sampling Theory

Concepts of population and sample. Concepts of Random Sample and Statistic. Sampling Distribution.

4. Elements of Estimation Theory

Concept of Estimator. Point and Interval Estimates. Confidence Intervals for a mean, for a proportion, for a difference of means and for a difference of proportions.

5. Parametric Hypothesis Testing

Concepts of null and alternative hypothesis, critical region, significance level, decision rule of the test, errors type I and type II and power of the test.

6. Simple Linear Regression

Regression line. Parameter estimation of best linear fit using the least squares approach.

Concept of residuals. Empirical linear correlation coefficient.

Bibliografia Obrigatória

Folhas editadas pelo Departamento de Matemática; (disponíveis no Moodle)
Murteira, B.; Ribeiro, C. S.; Andrade e Silva, J.; Pimenta, C.; Introdução à Estatística, 2ª edição, McGraw-Hill, 2008
Murteira, B.; Antunes, M.; Probabilidades e Estatística, Volumes 1 e 2, Escolar Editora, 2012
Montgomery, D.; Runger, G.; Applied Statistics and Probability for Engineers,5th ed., ,John Wiley & Sons, 2011

Bibliografia Complementar

André, J.; Probabilidades e Estatística para Engenharia, Lidel, 2018
Galvão de Melo, F.; Probabilidades e Estatística: conceitos e métodos fundamentais, Volumes 1 e 2, Escolar Editora, 2000 (2ª edição, vol. 1) e 1997 (vol. 2)
Reis, E.; e outros; Estatística Aplicada, Volumes I e II (4ª edição), Edições Sílabo, 2003
Robalo, A.; Estatística - Exercícios, Volumes 1 e 2 (5ª edição, 2ª reimpressão), Edições Sílabo, 2001

Métodos de ensino e atividades de aprendizagem

Classroom lectures through a combination of lecture method and problem solving.

E-learning in the Moodle platform and Microsoft Teams, providing access to the contents of UC through several materials, promoting the holding of weekly activities.

Tipo de avaliação

Distributed evaluation with final exam

Componentes de Avaliação

Designation	Peso (%)
Exame	100,00
Total:	100,00

Componentes de Ocupação

Designation	Tempo (Horas)
Estudo autónomo	86,00
Frequência das aulas	22,00
Total:	108,00

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 4 smalll tasks.

Exam Evaluation

Evaluation by final examination.

Fórmula de cálculo da classificação final

Continuous Evaluation

Assigning by MT the average of the tests (from zero to 20) and by MMF the average of the small tasks (from zero to 20), the final classification (CF) is:

CF = máximo{0.7×MT+0.3×MMT; MT}

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

- 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 than 9.5 values.

Exam Evaluation

-If the grade of the exam is greater than 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 to 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

All information about the course, including support materials, is available on the Moodle platform.

Recomendar Página Voltar ao Topo