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Statistical Methods for Linguistics and Psychology

Welcome to The 3rd Summer School on Statistical Methods for Linguistics and Psychology, SMLP 2019!

  • Application deadline:
    EXPIRED for 2019!
  • Timeframe:
    09 - 13th, September 2019
  • Location:
    Campus Griebnitzsee, University of Potsdam

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”.

  • Application deadline:
    EXPIRED for 2019!
  • Timeframe:
    09 - 13th, September 2019
  • Location:
    Campus Griebnitzsee, University of Potsdam


Curriculum

Instructors

Daniel Schad

Audrey Buerki

(maximum 30 participants)

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

Instructors

Daniel Schad

Audrey Buerki

(maximum 30 participants)

Instructors

Shravan Vasishth

Bruno Nicenboim

(maximum 30 participants)

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

Instructors

Shravan Vasishth

Bruno Nicenboim

(maximum 30 participants)

Instructors

Reinhold Kliegl

Daniel Schad

Audrey Buerki

Douglas Bates

(maximum 30 participants)

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

Instructors

Reinhold Kliegl

Daniel Schad

Audrey Buerki

Douglas Bates

(maximum 30 participants)

Instructors

Bruno Nicenboim

Shravan Vasishth

(maximum 30 participants)

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)

Instructors

Bruno Nicenboim

Shravan Vasishth

(maximum 30 participants)