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Presentation
Presentation
Statistical methods are a fundamental tool for analyzing and interpreting data.This course presents the basics of statistical thinking, language, and techniques. Students should be able to recognize the usefulness and wide application of these methodologies to various contexts, particularly in their subject areas.
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Class from course
Class from course
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Degree | Semesters | ECTS
Degree | Semesters | ECTS
| Anual | 2
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Year | Nature | Language
Year | Nature | Language
1 | Mandatory | Português
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Code
Code
ULHT125-3441
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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
1. Introduction
2. Data analysis
- Introduction
- Data types
- Graphical representation
3. Sample measures
- Location measurements (average, median, mode, quantiles)
- Dispersion measures (sample amplitude, interquartile dispersion, variance, standard deviation)
4. Probability
- Algebra of events and properties.
- Probability Concepts
- Kolmogorov's Axiomatic and its consequences
- Conditioned probability.
- Independent events
5. Discrete models
- Binomial
- Poisson
6. Continuous models
- Gaussian
- Weibull
7. Reliability
- Definition
- Systems reliablity
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Objectives
Objectives
- Understand the concepts of Descriptive Statistics and Inductive Statistics, identify them and apply them in practical cases.
- Have knowledge about how to obtain, classify and analyze samples and how to do the respective statistical treatment.
- Internalize the concepts of algebra of events.
- Know the various concepts of probability and learn how to compute the probability of events.
- Properly identify probability distribuition models
- Understand the definition of reliability and its application to different types of systems
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Teaching methodologies and assessment
Teaching methodologies and assessment
The classes are theoretical-practical, the theoretical concepts are presented and then complemented with practical examples. Orientations are given for students' study and learning. For each topic, it is presented a set of exercises of application of the theoretical concepts to concrete problems for students to solve in class and the final resolution is presented. The evaluation is through final examination.
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References
References
Câmara, A.M. (1996) – Matemática - 10º Ano – 3ºVol. Rumo
Murray, R: S.(1977) – Probabilidade e Estatística. McGraw-Hill.
Murteira, B. J. – Probabilidades e Estatística. McGraw-Hill.
Santos, F.B. (1989) – Sebenta de Matemática – Estatística. 4ªEd.
Meyer, P. L. (1983) – Probabilidade. Aplicações à Estatística. (2ª edição) Livros Técnicos e Científicos Editora.
Oliveira, J. Tiago - Probabilidade e Estatística (Vol. I e II) McGraw-Hill.
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Office Hours
Office Hours
Nome do docente
Horário de atendimento
Sala
Ana Sofia Soares
A combinar com os alunos
Sala dos professores.
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Mobility
Mobility
No
