| Code | Type | Head of UE | Department’s contact details | Teacher(s) |
|---|---|---|---|---|
| US-B2-SCBIOL-006-M | Compulsory UE | GROSJEAN Philippe | S807 - Ecologie numérique des milieux aquatiques |
| Language of instruction | Language of assessment | HT(*) | HTPE(*) | HTPS(*) | HR(*) | HD(*) | Credits | Weighting | Term |
|---|---|---|---|---|---|---|---|---|---|
| Français | 0 | 0 | 0 | 0 | 0 | 6 | 6 |
| AA Code | Teaching Activity (AA) | HT(*) | HTPE(*) | HTPS(*) | HR(*) | HD(*) | Term | |
|---|---|---|---|---|---|---|---|---|
| S-BIOG-006 |
Objectives of general skills
- Acquire, understand and use knowledge in the fields of biology and other fields
- Understand and use mathematical tools and basic statistics to describe and understand biological concepts
- Solve issues relevant to biology
- Analyse and interpret, in an appropriate way, biological data collected in natura, through dissection or based on an experimental protocol in the laboratory
- Apply a scientific approach and critical thinking
- Understand and apply the basic principles of reasoning (obtaining data, analysis, synthesis, comparison, rule of three, syllogism, analogy, etc.)
- Understand the statistical and/or probabilistic methods
- Work with efficiency / accuracy / precision
- Present a hypothesis and hypothetical-deductive reasoning
- Develop critical thinking, test and monitor conclusions understanding the domain of validity, and explore alternative hypotheses
- Manage doubt and uncertainty
- Communicate effectively and appropriately in French and English
- Communicate in French, orally and in writing, the results of experiments and observations by constructing and using graphs and tables
UE's Learning outcomes
To be able to analyse correctly usual biological data in practice. This implies to master basic concepts in statistic and probability and to develop a potential to analyse a problem and to reformulate it in « statistical language », to apply statistical tools using a computer, and finally, to present results clearly and adequately in a scientific report.
UE Content
Descriptive statistics; Mean; Median; Standard deviation; Variance; Q-Q plot; Boxplot; Histogram; Statistical population; Sampling; Inference; Probabilities; Statistic distribution; Central limit theorem; Confidence interval; Hypothesis test; Parametric and non parametric tests; Simple linear regression; Binomial, Poisson, Chi-2, Normal, Student t and F distributions; Student t-test; One factor ANOVA; Wilkoxon-Mann-Withney test, Kruskal-Wallis test; Correlation; Pearson; Spearman; R software.
Prior experience
Bases in calculus, including logarithm and exponential, cartesian coordinate system and elementrary geometry in 2D and 3D.
Term 1 for Integrated Assessment - type
- Written examination
- Quoted exercices
Term 1 for Integrated Assessment - comments
Term 2 for Integrated Assessment - type
- Written examination
- Quoted exercices
Term 2 for Integrated Assessment - comments
Term 3 for Integrated Assessment - type
- Written examination
- Quoted exercices
Term 3 for Integrated Assessment - comments
Resit Assessment for IT - Term 1 (B1BA1) - type
- Written examination
- Quoted exercices
Resit Assessment for IT - Term 1 (B1BA1) - Comments
Type of Teaching Activity/Activities
| AA | |
|---|---|
| S-BIOG-006 |
Mode of delivery
| AA | |
|---|---|
| S-BIOG-006 |
Required Reading
| AA | |
|---|---|
| S-BIOG-006 |
Required Learning Resources/Tools
| AA | |
|---|---|
| S-BIOG-006 |
Recommended Reading
| AA | |
|---|---|
| S-BIOG-006 |
Recommended Learning Resources/Tools
| AA | |
|---|---|
| S-BIOG-006 |
Other Recommended Reading
| AA | |
|---|---|
| S-BIOG-006 |