Statistical Methods for Linguistics and Psychology

Keynote lectures/ The following are confirmed speakers:

• Julia Haaf, on modeling individual differences 
• Douglas Bates, title to be announced
• Reinhold Kliegl, title to be announced
• Paul Buerkner, ordinal regression

Funding: This summer school is funded by the DFG and is part of the SFB “Limits of Variability in Language”.

Introductory frequentist statistics

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 

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 

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
• [If there is demand] Some new developments in linear mixed modeling in Julia

Advanced Bayesian methods 

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)