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Statistical Methods

Code: EIC0105     Acronym: MEST

Classification Keyword
OFICIAL Mathematics

Instance: 2014/2015 - 2S

Active? Yes
Web Page: http://paginas.fe.up.pt/~jlborges/statistics/mest-2015.html
Responsible unit: Department of Industrial Engineering and Management
Course/CS Responsible: Master in Informatics and Computing Engineering

Cycles of Study/Courses

Acronym No. of Students Study Plan Curricular Years Credits UCN Credits ECTS Contact hours Total Time
MIEIC 189 Syllabus since 2009/2010 1 - 5 56 135

Teaching Staff - Responsibilities

Teacher Responsibility
José Luís Cabral Moura Borges

Teaching - Hours

Lectures: 2,00
Recitations: 2,00
Type Teacher Classes Hour
Lectures Totals 1 2,00
José Luís Cabral Moura Borges 2,00
Recitations Totals 7 14,00
António Carlos Corte-Real de Sousa 4,00
José Luís Cabral Moura Borges 6,00
Pedro Sanches Amorim 4,00

Teaching language



This course unit aims to provide students with an integrated vision of the basic concepts and techniques of Statistics.

Learning outcomes and competences

At the end of this course unit, students should be capable of:

-using methods to explore, summarize and present data;

- using statistical inference methods.

Working method



1. Scope and method of Statistics 2. Descriptive Statistics: characterisation of univariate and bivariate samples constituted by quantitative or qualitative data 3. Elementary probability theory 4. Random Variables and Probability Distributions: distribution of discrete and continuous variables; distribution parameters; transformed variables; 5. Joint Distribution of Two Random Variables: Joint, marginal and conditional distributions; Independent variables; Covariance and correlation; Distribution of functions of two or more random variables; 6. Characterisation of some univariate discrete distributions: Binomial, Hypergeometric and Poisson 7. Characterisation of some univariate continuous distributions: uniform, negative exponential, normal, chi-square, t and F; 8. Random Sampling and Sampling Distributions: distribution of a sample average; central limit theorem; generation of random variables 9. Confidence intervals: specification of confidence intervals; 10. Hypothesis Testing: Specification of hypothesis tests

Mandatory literature

Guimarães, Rui Manuel Campos; Estatística. ISBN: 978-84-481-5589-6
Rui Campos Guimarães e José António Sarsfield Cabral; Estatística, 2ª edição, Verlag Dashofer, 2011. ISBN: 978-989--642-108-3
Deborah Rumsey; Statistics Essentials FOR Dummies, wiley, 2010. ISBN: 978-0-470-61839-4

Complementary Bibliography

Wonnacott, Thomas H.; Introductory statistics. ISBN: 0-471-51733-X
Rui Campos Guimarães, José A. Sarsfield Cabral; Estatística. ISBN: 978-84-481-5589-6

Teaching methods and learning activities

Theoretical classes: presentation of the course unit themes followed by examples and problem solving Theoretical-practical classes: problem solving and clarification of doubts

Evaluation Type

Distributed evaluation with final exam

Assessment Components

Designation Weight (%)
Participação presencial 0,00
Exame 70,00
Teste 30,00
Total: 100,00

Amount of time allocated to each course unit

Designation Time (hours)
Estudo autónomo 72,00
Frequência das aulas 56,00
Total: 128,00

Eligibility for exams

Students cannot miss more classes than allowed by the rules. Students have to reach a minimum average grade of 6.00 in the mini-tests, in order to be admitted to the final exam.

Calculation formula of final grade

Final Grade= MT1 * 0.15 + MT2 * 0.15 + Exam * 0.70

In order to be approved it is necessary to have:

(MT1 + MT2)/2 >= 6.00

Exam >= 8.00

Special assessment (TE, DA, ...)

Students who do not need to attend classes (according to the rules) will be assessed based on the grade of the final exam. However, students can decide to attend the mini-tests (the professor must be informed) and their grade will be based on the following formula: MT1 * 0.15 + MT2 * 0.15 + Exam * 0.70 If students choose to be assessed by mini-tests and final exam, they will have to reach a minimum average grade of 6.00 in the mini-tests, to be admitted to the final exam.

If a student decides to attend the first mini-test it means that they will be assessed based on the continuous assessment rules, therefore they will have to attend both mini-tests.

Classification improvement

Students can improve the mark of their mini-tests at recurso (resit) season. However, this is only possible for students who completed the course at the normal season. Thus, students who want to improve their marks, have to reach a minimum grade of 9.5 out of 20 in the weighted average of the mini-tests and the regular season exam grade. If that is the case, the mini-tests grades will not be taken into account at the recurso (resit) season and the final grade will be solely based on the grade of the final exam.

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