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Summer School on Statistical Methods for Linguistics and Psychology, 9-13 September 2019, University of Potsdam, Germany

Publish Date: Jan 15, 2019

Deadline: Apr 01, 2019

Event Dates: from Sep 09, 2019 12:00 to Sep 13, 2019 12:00

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)


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.

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