Statistics and Data Analysis for Environmental Sciences

The aim of this course is to acquire the basics of data representation and analysis in the environmental field. The statistical concepts needed to characterize a state or an evolution will be studied, including data structures and the interpretation of results. Analytical tools used in environmental sciences and ecology will be covered through case studies, including: - analysis of hydrogeological, geochemical and geophysical data, etc. - concepts will be put into practice using Excel and xlstat tools. A project will validate the knowledge acquired on an environmental application.
Minimum skills to be acquired:Students must master the tools of inferential statistics and data processing. They must be able to choose the most appropriate processing methods for analyzing data typically relating to the environmental sciences.

Basic concepts of probability and statistics

I. Statistics applied to environmental sciences (14h)Review of basic statistical concepts: Random variables and probability laws (normal law, Poisson's law). Sampling (estimators, confidence interval of the mean). Descriptive statistics (estimators of mean, variance, etc.). Comparison of means and variancesCorrelation, simple and multiple linear regression (method of least squares).
II. Data analysis applied to environmental sciences (16h)Factor analysis: Principal component analysis. Discriminant factor analysis. Factorial correspondence analysisAutomatic classification

Statistics and data analysis