Fundamentals of Biostatistics

Code: MAT15197I

3 ECTS

Duration: 15 weeks/78 hours

Scientific Area: Mathematics

Teaching languages: Portuguese

Languages of tutoring support: Portuguese

Regime de Frequência: Presencial

Sustainable Development Goals

3. Saúde de qualidade - Assegurar uma vida saudável e promover o bem-estar para todos, em todas as idades.

4. Educação de qualidade - Assegurar a educação inclusiva, e equitativa e de qualidade, e promover oportunidades de aprendizagem ao longo da vida para todos.

12. Produção e consumo sustentáveis - Assegurar padrões de produção e de consumo sustentáveis.

14. Proteger a vida marinha - Conservação e uso sustentável dos oceanos, dos mares, e dos recursos marinhos para o desenvolvimento sustentável.

15. Proteger a vida terrestre - Proteger, recuperar e promover o uso sustentável dos ecossistemas terrestres, gerir de forma sustentável as florestas, combater a desertificação, deter e reverter a degradação da Terra e deter a perda da biodiversidade.

Learning Goals

It is intended that students know the essential topics of Probabilities and Statistics that allow them to understand the statistics used in their area of expertise, enabling the subsequent application of appropriate analysis techniques and the consequent interpretation of results.
Provide the necessary conditions for the proper use of statistical software.
Skills:
- Ability to critically select and organize information;
- Ability to apply various statistical tools in different contexts to aid decision-making;
- Ability to interpret the results critically;
- Ability to use statistical software rationally.

Exploratory Data Analysis
Main probability distributions
Confidence intervals and hypothesis tests for one and two populations.
Introduction to analysis of variance and assumptions validation

Teaching Methods

The teaching sessions are theoretical-practical, combining the concepts with their application to concrete veterinary medicine cases, including practical exercises to consolidate the fundamental concepts. The remaining sessions will be purely computer-assisted practice using real data, with the students actively participating in their analysis and discussion, with the outputs always being interpreted critically. Students are encouraged to solve problems with data from this area on their own in order to develop autonomy.

Assessment

The evaluation will be made in accordance with paragraph 11 of article 110 of the RAUE, considering the 2 evaluation regimes foreseen: Continuous (with 2 frequencies) or Final (per Exam). The final grade (NF), for students who obtain at least 8.0 points, in each of the frequencies, will be obtained according to the following weighting NF=0.50*F1+0.50*F2, where: F1 = Grade in the 1st frequency (50%). F2 = Grade in the 2nd frequency (50%). If the NF result is greater than or equal to 9.5, even with a grade lower than 8.0 in the 2nd frequency, the classification of the normal season will be 9 values. The use of AI tools is allowed in this course as technical, analytical and learning support, as long as students understand, validate and take full responsibility for the results produced. The misuse of sources, data or results constitutes a serious violation of academic integrity. It is unacceptable to use AI in assessments or exams without authorization. Misuse will be classified as academic fraud under Article 119 of the Academic Regulations (Code of Conduct, Fraud and Plagiarism). In case of plagiarism, the test will be invalidated and participation will be made superiorly. If deemed necessary to verify the extent to which the student has developed the knowledge and skills foreseen for the curricular unit, the student may be called for an oral test, under the terms of paragraph 13 of article 110 of the Academic Regulation of the University of Évora, and the conditions provided for in paragraph 4 of article 116 and paragraph 1 of article 118 of the same Regulation are ensured.