Crash Course in Statistics for Neuroscience Center Zurich

An annual course for students of the ZNZ to get hands-on acquaintance with statistics and its application to research. The goal of this course is to establish basic concepts required for good statistical practice and to give insights into the statistical programming environment R using RStudio and reporting tools such as Rmarkdown. Using real world examples we will show possibilities, limitations, and caveats of using statistics in neurosciences and research in general. This course gives 2 ECTS credit points. If you miss more than 3h there will be no credits awarded.

Date and time

June 26 - 30, 2017, 09:00 - 16:00 (CEST) at University Campus Irchel (Y27 H35/36).

Requirements

  • BSc/MSc/PhD/MD in natural sciences, pharmacy or medicine
  • one semester of introductory probability theory and statistics

Registration/Administration

Heidi Gauss, hgauss@neuroscience.uzh.ch, Tel. 044 635 33 82

Aims of the Crash Course

Participants will come to...
  • Have a basic knowledge of statistics
  • Gain familiarity with R and Rstudio, as well as R packages from CRAN
  • Develop a sense for good data visualization
  • Use R to produce customized plots
  • Scrutinize statistical results in publications
  • Use R to perform – and interpret! – commonly used statistical hypothesis tests
  • Fit linear models/ANOVAs to suitable data, check model assumptions and interpret the respective R output

The way we teach

  • The crash course will consist of 5 parts. Each part will start with two hours of theory, followed by a publication case study for the introduced topic, and then the participants will work among themselves in the afternoon
  • Theoretical parts will always be using real world examples from neurosciene publications to put concepts into context
  • Please bring your own laptop and ensure that you have an internet connection at the venue, power supply is available
  • Install R & RStudio - there are many guides on the internet on how to do it
  • A script containing documentation, comments and exercises will be made available for download at the beginning of the course
  • The lecturer will be coaching the participants on the tasks they will solve such that everyone can work with their own speed of learning to use R

Course material

The course materials are online and will be made available on the first day of the course.

Schedule


The schedule will be released soon.

Literature

The following list of books is not required for this course, but we strongly recommend their lecture.

Questions

For questions regarding the topic and teaching of the course contact Daniel Stekhoven, Tel. 044 632 21 61.

Questions regarding registration and administration of the course contact Heidi Gauss, Tel. 044 635 33 82.