66756 - Experimental Design and Data Analysis

Course Unit Page

Academic Year 2018/2019

Learning outcomes

At the end of this course the student knows the principal concepts of experimental design to plan and to analyse results from field and laboratory experiments. The student should be able to discriminate natural variability and anthropogenic impacts on different marine populations and communities. Moreover he/she should able to manage data matrices by using uni- and multivariate statistical techniques

Course contents

Experimental design. Introduction to Analysis of variance: single factor,nested design, factorial design. Factor effets, assumptions. Multifactor analysis of variance: nested design, factorial designs. Design to analyse environmental impacts. Introduction to correlation and regression. Introduction to mutivariate analyses: multivariate data, multivariate distance and dissimilarity measures. Introduction to cluster and ordination methods. Statistical test on multivariate data. Relationship between biotic and environmental data


Experimental Design and Data Analysis for Biologists - Gerry P. Quinn and Michael J. Keough - Cambridge University Press

Copies of the slides of the lectures

Teaching methods

Frontal lectures

Laboratory practicals

Assessment methods

Written test. The questions are intended to evaluate if the candidate has the basic knowledge of the arguments illustrated in the course

Teaching tools

Power point slides. Data analysis in computer room

Office hours

See the website of Marina Antonia Colangelo