First cycle
degree courses
Second cycle
degree courses
Single cycle
degree courses
School of Science
Course unit
SCP9088338, A.A. 2019/20

Information concerning the students who enrolled in A.Y. 2019/20

Information on the course unit
Degree course Second cycle degree in
IF0360, Degree course structure A.Y. 2013/14, A.Y. 2019/20
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Number of ECTS credits allocated 6.0
Type of assessment Mark
Website of the academic structure
Department of reference Department of Biology
E-Learning website
Mandatory attendance
Language of instruction Italian
Single Course unit The Course unit can be attended under the option Single Course unit attendance
Optional Course unit The Course unit can be chosen as Optional Course unit

Teacher in charge LORENZO MARAGONI 000000000000
Other lecturers CARLOTTA MAZZOLDI BIO/06

Course unit code Course unit name Teacher in charge Degree course code

ECTS: details
Type Scientific-Disciplinary Sector Credits allocated
Core courses BIO/07 Ecology 2.0
Core courses SECS-S/02 Statistics for Experimental and Technological Research 4.0

Course unit organization
Period First semester
Year 1st Year
Teaching method frontal

Type of hours Credits Teaching
Hours of
Individual study
Laboratory 2.0 32 18.0 No turn
Lecture 4.0 32 68.0 No turn

Start of activities 30/09/2019
End of activities 18/01/2020
Show course schedule 2019/20 Reg.2013 course timetable

Examination board
Examination board not defined

Prerequisites: No prerequisites are required to attend the course
Target skills and knowledge: The course is organized in two integrated parts.
The first part of the course aims at giving to the students the instruments to develop a sampling design, to choose the most appriate sampling tools to implement the sampling in relation to the type of habitat, study organism or community.
The second part of the course aims to give the basic knowledge on the statistical analyses applied to the researches in ecology, biology and environment.
At the end of the course, the students will achieve the expertise to:
1) develop a proper sampling design;
2) critically discuss case studies;
3) choose the statistical techniques more suitable to the aims of the research and how to apply the analyses using statistical software. Moreover, the students will learn the description, interpretation and discussion of the results.
Examination methods: The evaluation includes two parts, according to the two parts of the course.
The first part of the evaluation includes: a written exam with an open question on the topics presented during the course, a question on the application of the tools learnt during the course to a case study, and an oral presentation on case studies from scientific literature.
The second part is constituted by a practical exam in informatics lab.
The finale score is the average of the scores of the two parts.
Assessment criteria: The evaluation criteria include:
1) comprehension and knowledge of the topics of the course;
2) correct application of theoretical bases to the development of experimental design;
3) ability to present and critically discuss case studies;
4) comprehension and correct application of statistica methods, through the use of statistical softwares;
5) logical order, capacity of synthesis and use of the correct terminology in the presentation.
Course unit contents: First part (2 CFU + 1 CFU practical): the scientific method; types of problem; how to develop a sampling design; preliminary sampling; scale of variation of phenomena; precision, accuracy and bias; sample size; concept of minimal area and volume; concept of replicate and pseudoreplicate; types of sampling: random, systematic, stratified; allocations of sampling effort: simple, proportional optimal. Sampling methods and techniques used in different habitats; direct sampling and remote sensing: water column, bottom; monitoring and BACI; examples of manipulative experiments: factorial, nested. Discussion of case studies. Sampling in the field.
Second part (2 CFU +1 CFU practical): univariate and multivariate methods to evaluate association among biotic and abiotic variables, their relationships and presence of structures with gradients in experimental data. Specifically: inferential methods; multiple regression; principal component analysis and multi dimensional scaling.
Planned learning activities and teaching methods: he course includes: 1) lectures, 2)practical activities, 3)group work in the field, 4) presentation of a scientific paper.
1) Lectures provide the bases of the sampling methods and statistical analyses. During the lessons, the teachers use ppt files including texts, diagrams, images and videos. Student partecipation is promoted through questions and discussion and critical presentation of case studies based on scientific papers.
2) Practical activities are carried out inthe informatic lab, and include the application of the statistical analyses and the analyses of the data collected by the students.
3) the group work in the field aims at experimentally test different sampling designs to select the most appropriate. This activity is completed by the data analyses in the informatic lab.
4) Presentation of a scientific paper with a critical discussion of the applied sampling methods and design.
Additional notes about suggested reading: All files of theoretical and practical lessons, papers, and data files used during the practical activities are available in the e-learning platform:
Textbooks (and optional supplementary readings)
  • Whitlock M.C.& Schluter D., Analisi statistica dei dati biologici.. Bologna: Zanichelli, 2010. Cerca nel catalogo

Innovative teaching methods: Teaching and learning strategies
  • Lecturing
  • Loading of files and pages (web pages, Moodle, ...)

Innovative teaching methods: Software or applications used
  • Moodle (files, quizzes, workshops, ...)

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