Applied Statistics

Code:

M2026

Acronym:

M2026

Keywords
Classification	Keyword
OFICIAL	Mathematics

Instance: 2020/2021 - 2S

Active?	Yes
Responsible unit:	Department of Mathematics
Course/CS Responsible:	Master's Degree in Physical Engineering

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
L:F	0	Official Study Plan	2	-	6	56	162
			3
MI:EF	74	study plan from 2017/18	2	-	6	56	162

Teaching language

Portuguese

Objectives

Upon completing this course, the student should:

- have a good insight of the fundamental concepts and principles of statistics, and in particular those from basic inference statistics.

- know the common inference statistical  methods and how to apply them to concrete situations;

It is also expected that the student acquires familiarity with the programing language and software environment R, in the framework of problems solving.

Learning outcomes and competences

be able to identify and formulate a problem, to choose adequate statistical methods and to analyze and interpret in a critical way the obtained results.

Working method

À distância

Pre-requirements (prior knowledge) and co-requirements (common knowledge)

 

Program

1. Brief introduction to the objectives and methodology of statistics. 

2. Descriptive Statistics: definition of a statistic, types of observations and measurement scales; techniques for summarizing data (tables, graphs, measures of location and dispersion), outlier definition and the concept of correlation. 

3. Some probability distributions: discrete distributions (uniform, binomial, and Poisson) and continuous (uniform, normal, exponential, chi-square and t-student. F); de Moivre-Laplace and the Central Limit theorems.

4. Sample distributions.

5. Statistical inference:point estimation (main concepts and properties of estimators);  interval estimation (confidence intervals for the mean, difference in means, proportion, difference in proportions, variance); hypotheses tests (parametric and non-parametric).

Mandatory literature

Douglas C. Montgomery; Applied statistics and probability for engineers. ISBN: 0-471-17027-5
Christopher J. Wild; Chance encounters. ISBN: 0-471-32936-3
Bento José Ferreira Murteira; Introdução à estatística. ISBN: 972-773-116-3

Complementary Bibliography

Casella George; Statistical inference. ISBN: 0-534-24312-6
Pestana Dinis Duarte; Introdução à probabilidade e à estatística. ISBN: 972-31-0954-9

Teaching methods and learning activities

Lectures and classes: The contents of the syllabus are presented in the lectures, illustrated with several examples. In the practical classes, exercises and related problems are solved and discussed. Several real data sets will be analyzed using the statistical software R. All resources are available for students at the unit’s web page.

 

Software

R

keywords

Physical sciences > Mathematics > Statistics

Evaluation Type

Evaluation with final exam

Assessment Components

designation	Weight (%)
Exame	100,00
Total:	100,00

Amount of time allocated to each course unit

designation	Time (hours)
Estudo autónomo	106,00
Frequência das aulas	56,00
Total:	162,00

Eligibility for exams

No requisites.

Calculation formula of final grade

In the two evaluation periods, the classification will be the one obtained in an exam with the quotation of 20 values, with the exception described below.

Exception applicable to both seasons: Students with a rating greater than or equal to 17.5 points may have to take a written or oral test to obtain a rating greater than or equal to 18 points. Otherwise, they will have the classification of 17 values.

Special assessment (TE, DA, ...)

Any type of special student evaluation may take one of the following forms: exclusively an oral examination; an oral examination plus a written examination, the student being required to pass both of them; only a written examination. The option for one of them is the sole responsibility of the course jury.

Observations

The Program and the evaluation rules may have to be modified if the FCUP guidelines for distance activities are to be changed.


Artigo 13º do Regulamento Geral para Avaliação dos Discentes de Primeiros Ciclos, de Ciclos de Estudos Integrados de Mestrado e de Segundos Ciclos da U.Porto, aprovado em 19 de Maio de 2010 (cf. http://www.fc.up.pt/fcup/documentos/documentos.php?ap=3&ano=2011): "A fraude cometida na realização de uma prova, em qualquer das suas modalidades, implica a anulação da mesma e a comunicação ao órgão estatutariamente competente para eventual processo disciplinar."

 

Any student may be required to take an oral examination should there be any doubts concerning his/her performance on certain assessment pieces.