Statistics and Probability

Code:

EEC0011

Acronym:

PEST

Keywords
Classification	Keyword
OFICIAL	Mathematics

Instance: 2012/2013 - 1S

Active?	Yes
Responsible unit:	Department of Electrical and Computer Engineering
Course/CS Responsible:	Master in Electrical and Computers Engineering

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
MIEEC	365	Syllabus (Transition) since 2010/2011	2	-	6	63	162
		Syllabus	2	-	6	63	162

Teaching language

Portuguese

Objectives

This course aims to endow students with underlying knowledge of Statistics and Probability, which is indispensable to take decisions in uncertainty situations that happen in various areas of Engineering.
This course also aims to endow students with accurate communication skills when themes in the domain of Statistics and Probability are referred. Students will also develop a critical attitude in the analysis of engineering problems and they will be able to apply their knowledge in the resolution of practical problems. The adequate learning of the fundamental concepts of this course will make students able to easily learn advanced knowledge in their future career, both academic and professional.

Learning outcomes and competences

Aquisition of a body of basic knowledge and the transmission of the very process of knowledge construction. The aim is to provide a solid preparation in mathematics skills in probabilities and statistics and prepare competences in mathematical modeling techniques fundamental for the processes of acquisition, processing and use of information.

Working method

Presencial

Program

1) Probabilities. Conditional probability and independence; Bayes’ theorem.

2) Random Variables; functions of random variables; most important distributions.

3) Sampling: Samples and sampling distributions.

4) Point estimate: Estimators and estimates; desirable properties of point estimates; estimation methods (method of least squares).

5) Interval estimate: Concept of confidence interval; specification of confidence intervals; sampling dimensioning.

6) Hypothesis testing: Introduction; hypothesis testing procedures; relationship between confidence intervals and hypothesis testing; dispersion and localization testing.

7) Introduction to stochastic processes: Notion of discrete stochastic processes; average and correlation of a discrete stochastic process; stationary stochastic processes; ergodic stochastic processes; white noise; Wiener’s model.

Mandatory literature

Douglas C. Montgomery, George C. Runger; Applied statistics and probability for engineers. ISBN: 0-471-74589-8
Douglas C. Montgomery, George C. Runger; Estatística aplicada e probabilidade para engenheiros. ISBN: 85-216-1360-1

Complementary Bibliography

Papoulis, Athanasios; Probability, random variables, and stochastic processes. ISBN: 0-07-100870-5
Guimarães, Rui Manuel Campos; Estatística. ISBN: 978-84-481-5589-6
Meyer, Paul L.; Probabilidade. ISBN: 85-216-0294-4
Isabel Ferreira; Probabilidades e Estatística, 2007
Ronald E. Walpole, Raymond H. Myers, Sharon L. Myers, Keying Ye; Probability and Statistics for Engineers and Scientists, Pearson Education International
Dimitri P. Bertsekas and John N. Tsitsiklis; Introduction to Probability, Athena Scientific

Teaching methods and learning activities

Theoretical-classes: presentation of the themes of the course illustrated by examples, which explain the concepts and results presented;

Theoretical-practical classes: exercises proposed and solved by the professor. Students will be encouraged to actively participate in class by suggesting solutions to the exercises and by criticizing results.

Evaluation Type

Distributed evaluation with final exam

Assessment Components

Description	Type	Time (hours)	Weight (%)	End date
Attendance (estimated)	Participação presencial	56,00
Exame	Exame	3,00	60,00	2013-02-08
short exams	Teste		40,00	2012-12-14
	Total:	-	100,00

Amount of time allocated to each course unit

Description	Type	Time (hours)	End date
Individual study	Estudo autónomo	78	2013-02-28
Attendance (estimated)	Frequência das aulas	56	2012-12-14
	Total:	134,00

Calculation formula of final grade

CF = 0,4* AD + 0,6 * EF
where:
- CF is the final mark (0 - 20)
- EF is the mark in the final exam (0 - 20).
- AD is the mark in the continuous evaluation (0 - 20)
In order to pass in this curricular unit, the student needs a minimum mark of 6 in 20 in the final exam.
The continuous evaluation include the resolution of two short exams.