| Title | Time | Room | Instructor |
|---|---|---|---|
| Experimental Design and Statistical Analysis for Life Scientists | 24.04.2023 08:45 - 10:00 (Mon) | Office Meeting room O1.101 big | Cremer, Sylvia |
| Experimental Design and Statistical Analysis for Life Scientists | 26.04.2023 08:45 - 10:00 (Wed) | Office Meeting room O1.101 big | Cremer, Sylvia |
| Experimental Design and Statistical Analysis for Life Scientists (recitation) | 26.04.2023 10:15 - 11:15 (Wed) | Big Seminar Room A (small) 27 seats | |
| Experimental Design and Statistical Analysis for Life Scientists | 03.05.2023 08:45 - 10:00 (Wed) | Office Meeting room O1.101 big | Cremer, Sylvia |
| Experimental Design and Statistical Analysis for Life Scientists (recitation) | 03.05.2023 10:15 - 11:15 (Wed) | Big Seminar Room A (small) 27 seats | |
| Experimental Design and Statistical Analysis for Life Scientists | 08.05.2023 08:45 - 10:00 (Mon) | Office Meeting room O1.101 big | Cremer, Sylvia |
| Experimental Design and Statistical Analysis for Life Scientists | 10.05.2023 08:45 - 10:00 (Wed) | Office Meeting room O1.101 big | Cremer, Sylvia |
| Experimental Design and Statistical Analysis for Life Scientists (recitation) | 10.05.2023 10:15 - 11:15 (Wed) | Big Seminar Room A (small) 27 seats | |
| Experimental Design and Statistical Analysis for Life Scientists | 15.05.2023 08:45 - 10:00 (Mon) | Office Meeting room O1.101 big | Cremer, Sylvia |
| Experimental Design and Statistical Analysis for Life Scientists | 17.05.2023 08:45 - 10:00 (Wed) | Office Meeting room O1.101 big | Cremer, Sylvia |
| Experimental Design and Statistical Analysis for Life Scientists (recitation) | 17.05.2023 10:15 - 11:15 (Wed) | Big Seminar Room A (small) 27 seats | |
| Experimental Design and Statistical Analysis for Life Scientists | 22.05.2023 08:45 - 10:00 (Mon) | Office Meeting room O1.101 big | Cremer, Sylvia |
| Experimental Design and Statistical Analysis for Life Scientists | 24.05.2023 08:45 - 10:00 (Wed) | Office Meeting room O1.101 big | Cremer, Sylvia |
| Experimental Design and Statistical Analysis for Life Scientists (recitation) | 24.05.2023 10:15 - 11:15 (Wed) | Big Seminar Room A (small) 27 seats | |
| Experimental Design and Statistical Analysis for Life Scientists | 31.05.2023 08:45 - 10:00 (Wed) | Office Meeting room O1.101 big | Cremer, Sylvia |
| Experimental Design and Statistical Analysis for Life Scientists (recitation) | 31.05.2023 10:15 - 11:15 (Wed) | Big Seminar Room A (small) 27 seats | |
| Experimental Design and Statistical Analysis for Life Scientists | 05.06.2023 08:45 - 10:00 (Mon) | Office Meeting room O1.101 big | Cremer, Sylvia |
| Experimental Design and Statistical Analysis for Life Scientists | 07.06.2023 08:45 - 10:00 (Wed) | Office Meeting room O1.101 big | Cremer, Sylvia |
| Experimental Design and Statistical Analysis for Life Scientists (recitation) | 07.06.2023 10:15 - 11:15 (Wed) | Big Seminar Room A (small) 27 seats | |
| Experimental Design and Statistical Analysis for Life Scientists | 12.06.2023 08:45 - 10:00 (Mon) | Office Meeting room O1.101 big | Cremer, Sylvia |
| Experimental Design and Statistical Analysis for Life Scientists | 14.06.2023 08:45 - 10:00 (Wed) | Office Meeting room O1.101 big | Cremer, Sylvia |
| Experimental Design and Statistical Analysis for Life Scientists (recitation) | 14.06.2023 10:15 - 11:15 (Wed) | Big Seminar Room A (small) 27 seats |
Description:
Statistics for Life Sciences gives an introduction into experimental design and important statistical test procedures, both providing conceptual background (during lectures) and hands-on guide for running the statistical tests in R (during recitations and homework).
Capacity:
6/20
Course Code:
C_BIO-4002_S23
Course instructor(s):
Sylvia Cremer
Course type:
Taught course
Course level:
Advanced/specialized
Primary Track:
Biology
Secondary Track(s):
Neuroscience
Course format:
On campus
Duration:
Half semester
ECTS:
3
Semester:
Spring 2
Minimum number of participants:
8
Target audience:
The course is meant for experimentalists in biological research.
Prerequisites:
at least basic knowldedge in R (eg R intro first semester)
Teaching format:
lectures, recitations, homework, final oral presentation
Assessment form(s):
regular assignments and final presentation
Grading scheme:
Numeric grades (1-5)
Course Category:
Credit Course
Academic Year:
AY 2022/23