## UE Statistics and probability for life sciences - STA331 -

Diplômes intégrant cet élément pédagogique :

### Descriptif

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