Crash Course in Statistics
Note: the course was moved to January 2021 due to the SARS-CoV-2 situation and turned into a virtual-only event.
About this course
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 upon successful completion of the daily exercises.
Date + Time
January 18 – 22, 2021, 09:00 – 16:00 (CET).
Format and platform
The course will be given as a virtual-only event. Details will follow soon.
Registration + Administration
Heidi Gauss, hgauss@neuroscience.uzh.ch, Tel. 044 635 33 82
Aims of the 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 I teach
- Each day of the course will cover a certain topic of statistics and its application in research.
- Daily structure:
- The day will start with a two hour theoretical session, followed by a case study of a neuroscience publication, where we see how the concepts are (ab)used in science.
- In the afternoon the concepts are motivated using R, where the participants will work among themselves. –
- Install R & RStudio – there are many guides on the internet on how to do it.
- A script containing documentation, comments and exercises, as well as the slides of the theoretical parts in the mornings, will be made available 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.
Course material
All course material will be available online during the course.
Schedule
| Time | Monday | Tuesday | Wednesday | Thursday | Friday |
|---|---|---|---|---|---|
| 09:15-11:00 | Why? | Random variables | Visualisation | Tests | Caveats |
| 11:15-12:00 | Case 1 | Case 2 | Case 3 | Case 4 | Case 5 |
| 13:00-16:00 | R? | Handling data | Plotting | Modelling | What next? |
Literature
The following list of books is not required for this course, but I strongly recommend their lecture anyway.
- The cartoon guide to Statistics by L. Gonick and W. Smith
- How to Lie with Statistics by Darrel Huff
- R Cookbook by Paul Teetor
- ggplot2: Elgant Graphics for Data Analysis by Hadley Wickham
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.