Biostatistics

Recommended Prerequisites

Mathematics. Knowledge on probabilities and descriptive statistics.

Teaching Methods

This curricular unit includes both theoretical and practical classes. Teaching of the theoretical component is focus on the acquisition of knowledge and skills on different methods of data analysis and experimental design in biology. In the practical component, students come into contact with different software tools and will apply the acquired knowledge when taking decisions leading to problem solving and how to plan experiments.

Learning Outcomes

This course aims to provide students with the essentials of data processing and experimental design in biology, through understanding and applying different methods of data analysis and using different statistical software.

Work Placement(s)

No

Syllabus

Theoretical program

1. Fundamentals of Biostatistics

2. Sampling and sampling distribution

3. Introduction to hypothesis testing and hypothesis testing for one and two populations: z-test and t-test for one population; t-test for independent and paired samples; non-parametric tests

4. Analysis of variance: calculation of the various sources of variability and construction of the variance table; different experimental designs, multiple comparison tests.

5. Linear Regression and Correlation: principles for the calculation of linear regression; regression validation and confidence limits of estimates; comparison of regression lines; linear correlation.

6. Goodness of fit tests and contingency tables

7. Basics of experimental design

Practical program

1. Familiarization with statistical software

2 . Hypothesis testing (two populations)

3 . Analysis of Variance

4 . Goodness of fit tests and contingency tables

5. Linear correlation and regression

Head Lecturer(s)

Vítor Hugo Rodrigues Paiva

Assessment Methods

Assessment
Mini Tests: 20.0%
Exam: 40.0%
Resolution Problems: 40.0%

Bibliography

Gotelli N. J. & Ellison A. M. (2018). A primer of ecological statistics (Second). Sinauer Associates.

Navarro DJ and Foxcroft DR (2022). learning statistics with jamovi: a tutorial for psychology students and other beginners. (Version 0.75). DOI: 10.24384/hgc3-7p15

Pagano M. Gauvreau K. & Mattie H. (2022). Principles of biostatistics (Third). Chapman and Hall/CRC.

Triola M. M. Triola M. F. & Roy J. (2024). Biostatistics for the biological and health sciences (Third). Pearson.

Whitlock M. & Schluter D. (2020). Analysis of biological data (Third). Macmillan Learning.

Zar J. H. (2020). Biostatistical analysis (6th Edition). Pearson Education.

Endereços de “internet” com informação relevante.

Glossário de termos estatísticos.

http://www.animatedsoftware.com/statglos/statglos.htm

http://www.basic.nwu.edu/statguidefiles/sg_glos.html

Conceitos e aplicações em Bioestatística.

http://faculty.vassar.edu/lowry/webtext.html