| Course Content || The application of statistical techniques is ubiquitous in quantitative neuroscience research. Knowledge of the basics of statistic is therefore essential for the correct understanding and interpretation of results published in the literature. Also, publishing and properly reporting the results of one's own research critically depend on statistical skills. This lecture will cover basic concepts important to experimentally working molecular neuroscientists, including descriptive statistics, hypothesis testing, and correlation and regression analysis. |
The aim of the lecture is to provide a toolkit for basic statistical analysis and an understanding of important statistical concepts. At the end, students are able to apply the basic techniques to data and acquire additional knowledge on their own. They will also be able to critically assess the statistical techniques used in publications and be aware of the most common pitfalls in the use of statistics.
The course consists of lectures, exercises at home, computer exercises in class and a small project, where a statistical problem must be solved independently and presented afterwards.
| Location and Time || Wednesday, 9:30 am - 11.15 am, Lecture Hall 2, Graduate School |
| Important Information || Download information sheet for details about times, exercises and grading. |
On days with computer exercises, the course will be 9.30-12.00.
For further information, visit the course website at the Graduate School of Cellular & Molecular Neuroscience.
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| Lecturer || Philipp Berens and Alexander Ecker |