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Code: | EEC0011 | Acronym: | PEST |

Keywords | |
---|---|

Classification | Keyword |

OFICIAL | Mathematics |

Active? | Yes |

Responsible unit: | Department of Electrical and Computer Engineering |

Course/CS Responsible: | Master in Electrical and Computers Engineering |

Acronym | No. of Students | Study Plan | Curricular Years | Credits UCN | Credits ECTS | Contact hours | Total Time |
---|---|---|---|---|---|---|---|

MIEEC | 357 | Syllabus (Transition) since 2010/2011 | 2 | - | 6 | 63 | 162 |

Syllabus | 2 | - | 6 | 63 | 162 |

Lectures: | 2,00 |

Recitations: | 2,00 |

Type | Teacher | Classes | Hour |
---|---|---|---|

Lectures | Totals | 2 | 4,00 |

Daniel Enrique Lucani Rotter | 2,00 | ||

Jaime dos Santos Cardoso | 2,00 | ||

Recitations | Totals | 8 | 16,00 |

Jaime dos Santos Cardoso | 4,00 | ||

Luís António Pereira de Meneses Corte-Real | 8,00 | ||

Daniel Enrique Lucani Rotter | 4,00 |

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.

Conditional probability and independence; Bayes’ theorem

2) Random Variables

One-dimensional and multidimensional random variables; functions of random variables; most important distributions (discrete and continuous)

3) Sampling

Samples and sampling distributions

4) Point estimate

Estimators and estimates; desirable properties if 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

Douglas C. Montgomery, George C. Runger; Estatística aplicada e probabilidade para engenheiros. ISBN: 85-216-1360-1

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

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.

Description | Type | Time (hours) | Weight (%) | End date |
---|---|---|---|---|

Attendance (estimated) | Participação presencial | 56,00 | ||

Total: |
- | 0,00 |

According to number 3 of paragraph 4 of General Evaluation Rules of FEUP, students with a special status (working-students, military personnel) do not need to attend to classes. Students who attended to this course in 2008/2009 do not need to attend classes either, and it will be considered their continuous assessment mark.

FM- Final Mark (from 0 to 20)

FE- Final Exam (from 0 to 20)

CA- Continuous Assessment (from 0 to 20)

Students have to reach a minimum mark of 30% in the final exam to complete the course (6 out of 20).

Continuous assessment will be based on 5 exercises.

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Page generated on: 2019-04-19 at 12:05:02

Page generated on: 2019-04-19 at 12:05:02