Third Summer School on Statistical Methods for Linguistics and Psychology, 2019, 9-13 September
Summer School Location
Griebnitzsee Campus, University of Potsdam, Germany
The summer school will be held at the Griebnitzsee campus of the University of Potsdam; this is about 15-20 minutes away from Berlin zoo station by train. Lectures will be held in Haus 6. Invited lectures will be held in Hoersaal H02.
Introductory frequentist statistics (maximum 30 participants)
Instructors: Daniel Schad and Audrey Buerki
Topics to be covered:
- Very basic R usage, basic probability theory, random variables (RVs),
including jointly distributed RVs, probability distributions,
including bivariate distributions
- Maximum Likelihood Estimation
- sampling distribution of mean
- Null hypothesis significance testing, t-tests, confidence intervals
- type I error, type II error, power, type M and type S errors
- An introduction to (generalized) linear models
- An introduction to linear mixed models
Introductory Bayesian statistics (maximum 30 participants)
Instructors: Shravan Vasishth and Bruno Nicenboim
Topics to be covered:
- Basic probability theory, random variable (RV) theory,
including jointly distributed RVs
- probability distributions, including bivariate distributions
- Using Bayes' rule for statistical inference
- Introduction Markov Chain Monte Carlo
- Introduction to (generalized) linear models
- Introduction to hierarchical models
- Bayesian workflow
Advanced frequentist methods (maximum 30 participants)
Instructors: Reinhold Kliegl, Daniel Schad, and Audrey Buerki
Topics to be covered:
- Review of linear modeling theory
- Introduction to linear mixed models
- Model selection
- Contrast coding and visualizing partial fixed effects
- Shrinkage and partial pooling
- Visualization
Advanced Bayesian methods (maximum 30 participants)
Instructors: Bruno Nicenboim and Shravan Vasishth
Topics will be some selection of the following topics:
- Review of basic theory
- Introduction to hierarchical modeling
- Multinomial processing trees
- Measurement error models
- Modeling censored data
- Meta-analysis
- Finite mixture models
- Model selection and hypothesis testing
(Bayes factor and k-fold cross-validation)
Funding
This summer school is funded by the DFG and is part of the SFB “Limits of Variability in Language”.
For more information click "LINK TO ORIGINAL" below.
This opportunity has expired. It was originally published here:
https://vasishth.github.io/smlp2019/