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Presentation
Presentation
Biomathematics and Statistics
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Class from course
Class from course
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Degree | Semesters | ECTS
Degree | Semesters | ECTS
Bachelor; Master Degree | Semestral | 5
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Year | Nature | Language
Year | Nature | Language
1 | Mandatory | Português
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Code
Code
ULHT477-3073
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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. Historical introduction 2. Probability Algebra of events Probability concept Simple and conditional probabilities 3. Elementary notions of differential and integral calculus Derivative: rules, partial derivatives, of higher order, total differential, chain rule Primitive and Integrals: properties, fundamental theorem, primitives techniques Differential Equations 4. Random variables (R.V.) Discrete and continuous Distribution function of a discrete and continuous R.V. 5. Parameters Mean, mode and median of a discrete and continuous R.V. Simple moments of discrete and continuous R.V. Variance and standard deviation of discrete and continous R.V. Simple moment of order r ∈ N of a discrete and continuous R.V. Central moment of R.V. discrete or continuous Moment-generating function Discrete and continuous R.V. 6. Discrete Distributions Binomial Hypergeometric Poisson 7. Continuous distributions Uniform Normal
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Objectives
Objectives
Biomathematics combines the simultaneous use of biomedical sciences and mathematics. The study and investigation of the life sciences frequently resort to the support of mathematical processes, and it is clear that mathematical interventions have made a decisive contribution to the progress of Science. This contribution has been made directly through the development of mathematical models describing living systems and the processes that occur in them, and also through the mathematical/statistical treatment of the results of biological experiments. Additionally, the computer has opened multiple paths to medicine, as has happened in other disciplines, allowing a wider application of methods and expeditious statistical treatment of data. Thus, students will gain a sense of the importance of statistics in scientific research and in everyday life, as well as apply different techniques of basic statistics to data processing and be prepared in the practice of statistics.
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Teaching methodologies and assessment
Teaching methodologies and assessment
The teaching-learning methodologies include several instruments, based on master classes/tutorials and face-to-face theoretical-practical classes. Other non presential instruments (e.g. moodle) complete and diversify the available options. The theoretical-practical classes are intended to deepen and exercise the subjects taught in the theoretical classes, thus providing a more direct contact with these subjects. The evaluation system is preferably continuous and consists of two written tests (50% each). The final exam regime applies to students who opt for it, students who fail the continuous assessment, and those who request a grade improvement, covering the entire program.
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References
References
Piskounov N., Cálculo Diferencial e Integral, Edições Lopes da Silva, 12 Ed., 1988. Apostol T. M., Cálculo, Ed Reverté, 1988. ISBN: 84-291-5014-5 Proença I. M. , Estatística , Lisboa: Euedito, 2010. ISBN: 978-989-20-2136-2. Martins M. E. G, Introdução à Probabilidade e Estatística com complementos de Excel. Departamento de Estatística e Investigação Operacional da FCUL, Sociedade Portuguesa de Estatística, 2005. https://www.spestatistica.pt/publicacoes/publicacao/introducao-probabilidade-e-estatistica. Cordeiro N., Magalhães A., Introdução à Estatística: Uma Perspectiva Química, LIDEL- Edições Técnicas Lda, Lisboa, 2004. ISBN: 978-972-757-276-2. Robalo, A. e Botelho M. C., Estatística – Exercícios Vol. I e II: 6 Ed. Ed. Sílabo. 2018, ISBN: 978-972-618-936-7
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Office Hours
Office Hours
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Mobility
Mobility
No
