UE Statistics and probability for life sciences - STA331 -

Diplômes intégrant cet élément pédagogique :


This course aims at acquiring the basics of descriptive and inferential statistics. It will deal in particular with methods of point estimation, estimation by confidence interval, and hypothesis testing in a parametric framework. The teaching in the form of lectures/tutorial is completed by practical work sessions on computer aimed at familiarising students with the handling of the R software for statistics.

Pré-requis recommandés

Basic knolwledge in mathematics: calculus, fractions, powers and percentages, sequence of real numbers, etc.

Compétences visées

  • Load, explore, and summarize graphically a set of data;
  • Understand what is a probabilistic model, discrete or continuous;
  • Perform simple computations on some basic models, in particular binomial and Gaussian;
  • Identify a probabilistic model from a practical situation;
  • Compute confidence interval estimates for proportions, means, and variances;
  • Formulate hypotheses, compute tests statistics and p-values, interpret results and make practical decisions;
  • Perform analyses of variance (anovas) under different models, and understand their outcomes;
  • Adjust simple linear models, compute predicted values, test goodness-of fit by an anova;
  • Use the R statistical software

Informations complémentaires

Lieu(x) : Grenoble
Langue(s) : Anglais