Applied Statistics, Part 1

• This ten-hour course will cover methods for estimating means and proportions by defining and computing confidence intervals.
• We will then discuss methods for hypothesis testing for means and proportions using rejection region, p-value and confidence interval approaches.
• The tools discussed in the class will be the most used ones in everyday work with experimental data (including z-test, t-test).
• The course won't refer to any particular software but people used to work with any given software are welcome to use it in order to solve the exercises.
• In this course, some emphasis will be put on mathematical derivations in order to understand why and how the estimators follow certain distributions. An elementary background in calculus is very helpful. Knowledge of Probability Theory will definitively help.
• At the end and during the course you will have access to the lecture notes and to unique and dedicated python scripts useful to understand and solve the exercises.

If you are interested in taking this course, you can express this preference in the pre-registration webform. Pre-registering does not that you have to take the course. We will send an email with more information about the schedule.