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Presentation
Presentation
Basic elements of probability and statistics applied to veterinary medicine.
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Class from course
Class from course
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Degree | Semesters | ECTS
Degree | Semesters | ECTS
Bachelor; Master Degree | Semestral | 4
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Year | Nature | Language
Year | Nature | Language
1 | Mandatory | Português
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Code
Code
ULHT478-24667
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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. Data collection and organization. Types of variables. 2. Introduction to sampling methods. 3. Descriptive statistics. 4. Basic notions of probabilities, random variables and examples of probability distributions. 5. Law of large numbers, distribution of the means of random samples, central limit theorem and estimation of confidence intervals. Statistical inference. 6. Introduction to hypothesis testing for means and proportions. Sampling from normal distributions, with known and unknown variances. 7. Statistical tests for categorical or qualitative variables. 8. Parametric tests. 9. Non-parametric tests. 10. Association measures. Pearson and Spearman correlation. Simple linear and logistic regression models. 11. Use of the internet and online bibliographic databases to search for technical and scientific documents. 12. Use of software to solve problems with the application of concepts covered in the theoretical component.
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Objectives
Objectives
1. Use statistical methodologies to gather and summarize data in the field of veterinary sciences and proceed to do their exploratory analysis. 2. Recognize the conditions underlying the applicability of the theoretical models used in statistical analysis, distinguishing the limits of each of these models. 3. Evaluate and interpret the results obtained, using statistical inference. 4. Distinguish between cause-effect relationships and relationships of statistical association between variables. 5. Apply basic skills of research and critical reading of technical and scientific documents. 6. Use statistical analysis software for: i) word processing, construction of tables, graphs; ii) store, capture, process, analyze data using spreadsheets (Microsoft Excel®) and a statistical software package (SPSS or similar); iii) interpretation of results and technical decision making; iv) search for documentation on the internet and online bibliographic databases.
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Teaching methodologies and assessment
Teaching methodologies and assessment
Expository and interactive classes, inverted classroom, jigsaw technique and its variants, concept maps. Use of computer programs for statistical analysis: Excel and SPSS. Supervised self-learning (practical classes): throughout the semester, students will work in groups (descriptive and inferencial analysis of data), in which they will aply the knowledge acquired in theoretical and theoretical-practical classes, for a total of 12 hours. This work will be supervised by the teachers.
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References
References
- Petrie, A. & Watson, P. (2013). Statistics for veterinary and animal sciences, (3rd Ed.). West Sussex: Wiley-Blackwell. - Daniel, W.W. (2009). Biostatistics: a foundation for analysis in the health sciences, (9th Ed.). NJ: J. Wiley & Sons. - Callegari-Jacques, S.M. (2004). Bioestatística ? Princípios e aplicações, (1.ª Ed. Reimp.). Porto Alegre: Artmed. - Brase, C.H. & Brase, C.P. (2011). Understandable statistics: Concepts and methods, (10th Ed.). Boston: Cengage Learning. - Glantz, S.A. (2012). Primer of biostatistics, (7th Ed.). McGraw-Hill. - Pereira, A. & Poupa, C. (2018). Como escrever uma tese, monografia ou livro científico usando o Word, (7.ª Ed.). Edições Sílabo. - Marôco, J. (2018). Análise estatística com o SPSS Statistics, (7.ª Ed.). Report Number. - Rayat, C.S. (2018). Statistical methods in medical research. Springer Singapore. - Oliveira, A.G. (2014). Bioestatística descodificada, (2.ª Ed.). Lisboa-Porto: LIDEL.
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Office Hours
Office Hours
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Mobility
Mobility
No
