COMPUTER SKILLS
cod. 13461

Academic year 2016/17
1° year of course - Second semester
Professor
Academic discipline
Indefinito/interdisciplinare (NN)
Field
Abilità informatiche e telematiche
Type of training activity
More
21 hours
of face-to-face activities
3 credits
hub: PARMA
course unit
in - - -

Learning objectives

On the completion of this course, the students will acquire skills for the understanding and presentation of ecological data, useful for professional activities, for dissertation projects and for further studies.
In particular, the students will understand the rationale behind the scientific method, will develop the ability to critically read the scientific literature and will be able to plan an experiment, both in the phase of sampling design and in the subsequent steps of data analysis.

Prerequisites

None.

Course unit content

This course introduces the basic concepts for the collection and analysis of biological and environmental data, and provides the opportunity to experience methods and instruments useful for the understanding of ecological systems.

Full programme

- The scientific method and the role of statistical analysis;
- The approaches to the investigation of ecological problems;
- The logic of hypothesis testing and the development of a research;
- The different types of variables and the choice of statistical models;
- Sampling design and samples selection;
- Methods and tools for data collection and processing;
- A protocol for explorative analysis of data;
- The procedures for applying statistical models to data;
- The interpretation and presentation of results;
- Some case studies and common problems.

Bibliography

During the course students will be provided with lecture notes and a reading list will be suggested.

Teaching methods

The course includes lectures and practical activities in the lab and in the field.

Assessment methods and criteria

Knowledge will be assessed by means of a practical test and a following oral examination.

Other information

For some activity is essential to have a laptop; during the course open source programs for data processing will be installed.