Exploratory and decisional data analysis

Basics of statistics

NC

Cours magistraux
1- What is an experimental data set?
2- The different types of variables.
3- Why call variables "random"?
4- The general case of variance. The special cases known in Biology.
5- Why and how to analyze variance?
6- Why and how to reduce the dimensions of a dataset?
Travaux Dirigés
1- In what form are the data, what structuring. What is missing?
2- Measuring, counting, categorizing and describing; essentially.
3- Between chance and necessity... The need to estimate what one cannot know.
4- The general model and the distributions most encountered in Biology (counts, exponential)
5- Mean and variance, graphic demonstration "with the hands". The other estimators (median, mode, max, min)
6- To go from dream to visualizable, computational and apprehensible reality.
Travaux pratiques
1- Practice of R and R-Studio.
2- The metalibrary " Tidyverse " and the library " ggplot2 ".
3- Structuring your data, long and wide...
4- How to search for information on an R function?
5- How to install a new library in R-Studio?
6- The principle of a " pipeline ". How to use it in R.
7- The principle of a layered graphic. How to build it in R.

NC