Statistics is a must-needed set of tools in experimental sciences. In almost every study, methods from statistics are necessary and their justification is required for a good level publication. Despite the availability of a number of powerful and sophisticated software, it is not always obvious what analysis approach is needed in any particular case if one does not have an introductory level background in the matter. This compact course will cover a few of the fundamentals in statistics.

 

The course will cover methods for estimating means and proportions by defining and computing confidence intervals. We will discuss methods for hypothesis testing for means and proportions using rejection region, p-value and confidence interval approaches. We will see how to use simple non-parametric and resampling methods, including ANOVA and simple linear regression.

 

In this course, we won't cover much of the mathematics behind the statistics but focus on examples and intuition. 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.

 

Everyone interested is welcome to join. This course will be available online only and will be delivered live in a compact form, for three days in the row, five hours per day around end of February. Registration to attend this course is compulsory.