Univariate and multivariate analysis

Univariate and multivariate analysis

  • ECTS

    5 credits

  • Component

    Collège Sciences et Technologies pour l’Energie et l’Environnement (STEE)


This short course introduces students to biostatistics as applied to ecotoxicological studies. The basic principles and methods used in biostatistics are covered in this short course. This includes the technical qualifications necessary for exploring, analysing and interpreting data from both controlled experiments, in particular standardized ecotoxicity tests, and field monitoring. Beyond conventional tests such as ANOVA and its variants, an overview of other less conventional approaches will be provided to broaden statistical toolbox and ensure students to make proper use of their data.

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Investigating ecotoxicological data.


At the end of this Unit, you should understand:

  1. Basics of experimental and sampling design.
  2. Main statistical approaches to monitor toxicants and estimate their effects on organisms.
  3. Assumptions and interpretation of statistical methods.
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Course parts

  • Univariate and multivariate analysis CMLecture22h
  • Univariate and multivariate analysis TDTutorial23h

Knowledge check

1st : continuous assessment

  • Laboratory work and report (100%)

2nd exam : oral presentation

By completion of University Unit Evaluation Questionnaire by students, annual assessment by Unit Coordinator.

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Topics covered include:

  • Basic use of R software.
  • Basic and advanced statistical approaches.
  • Uni- and multivariate statistics.
  • OECD guidance on the statistical analysis of ecotoxicity tests: no/lowest observed effect concentrations (NOEC/LOEC), dose-response, effective concentrations (ECx).
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Additional information

Work in autonomy: 10 to 20h

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At the end of this Unit, you should be able to:

  1. Choose the most appropriate statistical method to answer a specific question.
  2. Use R software to analyse data.
  3. Interpret statistical results.
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  • N. Gotelli. 2004. A primer of ecological statistics, Sinauer Associates, Sunderland, Massachusetts.
  • C. Dytham. 2003.          Choosing and using statistics : a biologist’s guide, Blackwell, Malden (MA).
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