In these lectures we cover some of the techniques in data analysis which have been developed in a cosmological context. We start by considering the general problem of estimating parameters from data, focusing on Monte Carlo Markov Chains (MCMC) for small catalogs. Then, we continue with the Fisher matrix formalism to analyse experimental setups before any data are taken. In fact, the Fisher matrix formalism can be of great help to test the requirements of an experiment in order to reach the desired accuracy on the final parameters that need to be tested.
We consider different experimental setups and in each topic will face the built-in of the numerical codes alongside with the theoretical recipes in order to properly construct the observables.
The last lecture will have a hands-on approach: the participants will choose the desired observable and will write their own code in their favored language.

• 07.10.2024: Introduction to statistics. Fisher matrix formalism and MCMC.
• 08.10.2024: Construction of the Fisher matrix and MCMC for various experiments
• 09.10.2024: Hands-on session.

All the codes shown during the lectures are in Python (preferred) and in Mathematica.