Class Biostatistics

Practical applications of statistical analyses encompass all areas of biology. In this CU, emphasis will be given to the practical component and students will be confronted with concrete problems.

1. Basic statistics: Distributions and associated analyses. Parameters for location and dispersion. Data transformation.

2. Sampling techniques: Quadrat method. Spatial pattern analysis: aggregated, regular or random. Sampling methods: random, capture-recapture and transects.

3. Analysis of variance (ANOVA): Introduction. 1-way ANOVA (fixed and random models). 2-way ANOVA (fixed, random or mixed crossed model, nested model). 3-way (or higher) ANOVA. Conditions of use. A posteriori analyses.

4. Correlation and regression: Simple linear correlation. Pearson coefficient. Simple regression analysis. Residuals plot.

5. Non-parametric statistics: Mann-Whitney analysis. Wilcoxon analysis. Kruskal-Wallis ANOVA. Spearman correlation.

The student is put in a real situation: real data to analyze, total freedom in the choice of the analysis to try and develop his capacity to choose the most apropriate, information availability similar to the situation a scientist would know in the laboratory.

- Sokal RR & Rohlf FJ (1995). Biometry. The principles and Practice of Statistics in Biological Research. 3^rd Ed., W. H. Freeman and Company, New York.

- Statistical tables provided.

- Free online documents.