Difference between revisions of "UNIL MSc course: Data Analysis I 2024"
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'''Prerequisites''' | '''Prerequisites''' | ||
| − | Students who follow this course should already have some basic knowledge in statistics and R equivalent to the one achieved by bachelor students at the University of Lausanne. To catch up, if needed, students can participate in dedicated R refresher sessions for Master students by F. Schütz. | + | Students who follow this course should already have some basic knowledge in statistics and R equivalent to the one achieved by bachelor students at the University of Lausanne. To catch up, if needed, students can participate in dedicated R refresher sessions for Master students by F. Schütz each Wednesday at 10:15 in GEN/C starting from 25.9.24. |
'''Resources''' | '''Resources''' | ||
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* 20.09.2024 9:00-11:00 Basic notions of probability theory, Central Limit Theorem ([https://docs.google.com/presentation/d/12JxTXy-eIRgr-5nnYoPlfLrYU2PFCn6JchC6--X6mzg Slides]) | * 20.09.2024 9:00-11:00 Basic notions of probability theory, Central Limit Theorem ([https://docs.google.com/presentation/d/12JxTXy-eIRgr-5nnYoPlfLrYU2PFCn6JchC6--X6mzg Slides]) | ||
| − | * 27.09. | + | * 27.09.2024 9:00-11:00 Important distributions and tests, sampling and estimates ([https://docs.google.com/presentation/d/1C69DRUiTT78p-ZNIDuMch3ZVU-SYktPxMzBFaZwxyfk Slides]) |
| − | * 05.10. | + | * 05.10.2024 9:00-11:00 Introduction to linear regression ([https://docs.google.com/presentation/d/1FQyKC8FlPQ7PFf1N4lkw8Qgov5pDir35rYUxPF0E41Y Slides]) |
| − | * 11.10. | + | * 11.10.2024 9:00-11:00 Introduction to mixed models and Cox models ([https://docs.google.com/presentation/d/1SULxWwjz_a90FsGzHnS9TppfL_ZK2o3e_Y4yr4FI6eQ Slides]) |
| − | The lectures are accompanied by supervised exercise sessions (see below). | + | The lectures are accompanied by supervised exercise sessions (see below). Both take place in Amphi/BIO. |
'''Exercises and grades''' | '''Exercises and grades''' | ||
This course has no oral or written exam; instead students must submit their solutions to exercises. | This course has no oral or written exam; instead students must submit their solutions to exercises. | ||
| − | There will be four sets of exercises - one for each lecture. The exercise corresponding to each lecture is discussed 11:15-12:00 right after the lecture to make sure all questions are clear. The exercises are due on Thursdays at 22:00, six | + | There will be four sets of exercises - one for each lecture. The exercise corresponding to each lecture is discussed 11:15-12:00 right after the lecture to make sure all questions are clear. The exercises are due on Thursdays at 22:00, six days after the lecture. They are discussed on the following day in the afternoon at 13:15-14:00. |
| − | For each question we indicate how many points one receives for a correct answer. | + | For each question we indicate how many points one receives for a correct answer. The grade of each exercise is the sum of these points truncated at 6. The final grade is the average of the grades from the three sets. |
| − | *[https://docs.google.com/document/d/ | + | *[https://docs.google.com/document/d/1iISklTVeCspifajtffreuimzVTe6xCkRw-0wbFLkm9I Exercise set #1] (due on 26.09.2024 22:00) |
| − | *Exercise set #2 (due on 03.10.2024 22:00) | + | *[https://docs.google.com/document/d/1y1a3BCqPYU7HnI61JbeiNvadaHap-ElXUf4Nzb4g5mI Exercise set #2] (due on 03.10.2024 22:00) |
| − | *Exercise set #3 (due on 10.10.2024 22:00) | + | *[https://docs.google.com/document/d/12-EFnkWZmsIgftW1KCV8sBIODrTrh5vtrT9wcPOpmZg Exercise set #3] (due on 10.10.2024 22:00) |
| − | *Exercise set #4 (due on 17.10.2024 22:00) | + | *[https://docs.google.com/document/d/1ZITMHvGisB21khbNE3IF-9SmMV7-zCvu0ay8jTxhwXs Exercise set #4] (due on 17.10.2024 22:00) |
| − | Submission should be done via Moodle, but you can also send your exercise to Sven.Bergmann@unil.ch in case this does not work. | + | Submission should be done via [https://moodle.unil.ch/course/view.php?id=31896 Moodle], but you can also send your exercise to Sven.Bergmann@unil.ch in case this does not work. |
Latest revision as of 15:49, 26 September 2024
Introduction This course is for MSc students both from the MLS and BEC master programs. The goal is to review fundamental notions in statistics and show how they are useful for basic data analysis challenges in biology.
Prerequisites Students who follow this course should already have some basic knowledge in statistics and R equivalent to the one achieved by bachelor students at the University of Lausanne. To catch up, if needed, students can participate in dedicated R refresher sessions for Master students by F. Schütz each Wednesday at 10:15 in GEN/C starting from 25.9.24.
Resources The following software is required for this course:
- a recent version of R (in doubt, simply download and install the latest version from the R website at https://stat.ethz.ch/CRAN/ -- many potential problems are solved by simply upgrading to the latest R version)
- RStudio (which you can download from http://www.rstudio.com/products/rstudio/download/)
Schedule and content This course includes four 2h frontal lectures:
- 20.09.2024 9:00-11:00 Basic notions of probability theory, Central Limit Theorem (Slides)
- 27.09.2024 9:00-11:00 Important distributions and tests, sampling and estimates (Slides)
- 05.10.2024 9:00-11:00 Introduction to linear regression (Slides)
- 11.10.2024 9:00-11:00 Introduction to mixed models and Cox models (Slides)
The lectures are accompanied by supervised exercise sessions (see below). Both take place in Amphi/BIO.
Exercises and grades This course has no oral or written exam; instead students must submit their solutions to exercises.
There will be four sets of exercises - one for each lecture. The exercise corresponding to each lecture is discussed 11:15-12:00 right after the lecture to make sure all questions are clear. The exercises are due on Thursdays at 22:00, six days after the lecture. They are discussed on the following day in the afternoon at 13:15-14:00.
For each question we indicate how many points one receives for a correct answer. The grade of each exercise is the sum of these points truncated at 6. The final grade is the average of the grades from the three sets.
- Exercise set #1 (due on 26.09.2024 22:00)
- Exercise set #2 (due on 03.10.2024 22:00)
- Exercise set #3 (due on 10.10.2024 22:00)
- Exercise set #4 (due on 17.10.2024 22:00)
Submission should be done via Moodle, but you can also send your exercise to Sven.Bergmann@unil.ch in case this does not work.
