Statistical Methods

Statistics and Quantitative Methods for the Life and Social Sciences using R

The course provides and introduction to the practical use of statistics and quantitative methods for analysing qualitative and quantitative environmental, social, and biological data. The course is focussed around R, the most versatile and popular statistical package among modern environmental scientists.

The course is in two parts, which take students from first principles, through data exploration, hypothesis testing, and regression modelling:

(i) An introduction to managing and exploring data [1 week; requirement: B.Sc degree]

– Rationale for statistical methods

– Study design

– Introduction to R (and Excel)

– Power analysis

– Data exploration (data storage, transformation, plotting and data reduction)

– Calculation and plotting of bootstrapped confidence intervals

(ii) An introduction to testing and empirical modelling [1 week; requirement: B.Sc. degree and prior experience of using R for basic data exploration]

– Hypothesis testing

– Endpoint adjustment

– Pairwise tests

– Frequency test

– Correlation and regression

– Generalised linear models

The course is held twice annually at Flamingo Land Theme Park and Zoo in North Yorkshire, UK, and at the Udzungwa Ecological Monitoring Centre in Morogoro Region, Tanzania. These are both very unique settings for this kind of course. Lunch and refreshments are provided as part of the fee. Budget accommodation is also available on site for course participants if required.

To register your interest and for latest information on prices and dates, e-mail

Forthcoming courses:

Essential statistics and research methods for natural scientists : 18th-22nd May, University of York

This is an introductory course into sampling, managing data and performing statistical analysis. The module is taught primarily using computational software called R, which is freely available and becoming the prominent software choice of natural scientists.

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