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Presentation
Presentation
Students will learn what is a stochastic process and how to deal with some specific processes
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Class from course
Class from course
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Degree | Semesters | ECTS
Degree | Semesters | ECTS
Bachelor | Semestral | 6
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Year | Nature | Language
Year | Nature | Language
2 | Mandatory | Português
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Code
Code
ULHT6634-23086
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Prerequisites and corequisites
Prerequisites and corequisites
Not applicable
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Professional Internship
Professional Internship
Não
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Syllabus
Syllabus
CP1: Stochastic Processes and their characterization CP2: Markov Chains CP3: Poisson processes
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Objectives
Objectives
developed by the students): LO1: Understand and characterize simple stochastic systems in general; LO2: Solve basic problems associated with Markov chains and the Poisson process.
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Teaching methodologies
Teaching methodologies
The teaching methodology includes the expository method (TM1) to present the necessary contents, the demonstrative (TM2) to illustrate its application to practical examples and the active one (TM3) for solving exercises. The assessment of knowledge is made by continuous assessment or written test of the final exam. Continuous assessment includes two written tests with a weight of 35% each, practical exercises throughout the semester (20%) and involvement in class (10%).
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References
References
Ross, S.M. (2014). Introduction to Probability Models. (11th ed.). Academic Press,New York Ross, S.M. (1996). Stochastic Processes. (2nd ed.). John Wiley & Sons.
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Assessment
Assessment
2 Testes (70%) + TPC (20%) + Participação em aula (10%) [Podem respecar testes em data de frequência final]
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Exame final
Exemplo:
Descrição
Data limite
Ponderação
Teste de avaliação 1
02-05-2024
35%
Teste avaliação 2
06-06-2024
35%
TPC
20% Frequência Final 24-06-2024 Respescar Exame Recurso 08-07-2024 100%
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Mobility
Mobility
No




