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570007 WS Methods in Statistics (2023W)
10.00 ECTS (6.00 SWS), SPL 57 - Doktoratsstudium Biologie mit Schwerpunkt Mikrobiologie und Umweltsyste
Continuous assessment of course work
Labels
ON-SITE
Registration/Deregistration
Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
- Registration is open from Tu 02.01.2024 09:00 to We 31.01.2024 12:00
- Deregistration possible until We 31.01.2024 12:00
Details
max. 20 participants
Language: English
Lecturers
Classes
Place: Seminarraum 2.1, UBB, Djerassiplatz 1
Date/Time: 19.2.2024-01.03.2024, 9:00-13:00. Note the last lecture on the 1st March falls formally in the 2024 summer term... but we'll do it anyway :-)
There is no "akademische Viertelstunde", we will start at 9 am sharp every day!
- Programming with R: Mon-Tue 19.02-20.02
- Think statistics! with R: Wed-Thu 21.02-22.02
- Scientific visualisation with ggplot: Fri 23.02
- Linear regression: Mon 26.02
- Analysis of Variance (ANOVA): Tue 27.02
- Nonlinear regression: Wed 28.02
- Generalised linear models (GLM): Thu 29.02
- Bayesian statistics intro: Fri 01.03
Information
Aims, contents and method of the course
Assessment and permitted materials
The course will be evaluated through participation efforts and homework exercises which can be completed online. There will be no final examination.
Minimum requirements and assessment criteria
Lecture attendance is mandatory.
For most lectures homework exercises will have to be completed afterwards.
For most lectures homework exercises will have to be completed afterwards.
Examination topics
Reading list
Association in the course directory
PhD
Last modified: Fr 16.02.2024 12:27
- R programming
- Statistics with R: sampling theory, distributions, hypothesis testing, testing "recipes"
- Linear models: linear regression, LASSO, Ridge regression, PCA, linearization
- Nonlinear models: nonlinear regression, model comparisons, local smoothing, GAM
- ANOVA: One-way and two-way ANOVA, ANOVA as regression, ANCOVA
- Generalized linear models: Binomial GLM, Poisson GLM, negative binomial GLM, OLS as Gaussian GLM
- Bayesian statistics: basic theory, parameter estimation, Bayesian Networks
- ggplot: principles of visualisation, ggplot basics, plotting recipesHands-on exercises will be done during the lectures on small data sets.
Detailed information on the course contents can be found at: https://training.vbcf.ac.at/training/datasci.phpPlease bring a laptop with internet access to the course!