Minds, Mechanisms and Interaction in the Evolution of Language -

Summer school

September Tutorial in Empiricism: Practical Help for Experimental Novices


In September, the Language Evolution and Interaction Scholars of Nijmegen (LEvInSoN group), based in the Language and Cognition Department at the Max Planck Institute for Psycholinguistics will be hosting a workshop about research in Language Evolution and Interaction (September 21-22).

As an addition to this workshop, we will be hosting a short tutorial series (Sept 20 & 23) covering experimental and statistical methods that should be of broad interest to a general audience. In this tutorial series, we will cover all aspects of creating, hosting, and analysing the data from a set of experiments that will be run live (online) during the workshop.

On the first day (September 20th), students will be led through the conception of an experiment exploring crossmodal perceptual biases. The morning sessions will include sections about aligning research questions with experimental design and data analysis, outlining the basics of the intended experiments, and a brief section on computational models and how they can be used to generate experimental predictions.

In the afternoon session, we will cover experimental workflows and trial structure, troubleshooting, and online deployment of experiments.

The experiments created on Day 1 will be run online during the workshop proper (Sept 21-22), and the tutorial will reconvene on September 23 to cover data analysis and visualisation. In the morning sessions of September 23rd, we will cover preparation and sanitation of data, some basics about the statistical logic underlying mixed effects models, and finally live analyse the results of the experiment, focusing on how to interpret and report results. Following this, we will have a brief session on further statistical procedures like bootstrapping, and some visualisation techniques for the results.

Finally, as a bonus session, after lunch we will have a modelling-focused session where we discuss how to use experimental data as input for Bayesian models to generate predictions for future experiments and to generalise results to larger populations of interacting agents.

Across all session we will make use of and provide guidance with a number of software packages, including R (and R Markdown), Python, Presentation, and jsPsych. For each stage of experiment design, hosting, and data analysis, we will make use of a single piece of software (Python for Trial Structuring, jsPsych for Deployment, R for statistical analysis, Python for modelling), but will provide additional online modules that run parallel wherever possible: e.g. we will include Python scripts that structure, implement, and analyse the results of the same experiment. Thus, whatever platforms are more relevant to each student will be given as complete of coverage as possible. 

Registration is free, but required. Spots are limited, and a waitlist will be established if necessary. 


A preliminary schedule can be found HERE.

Background and Rationale for the specific project can be found HERE.

Details of project development, including the software suggested for participation can be found HERE.


  • Alan Nielsen
  • Ashley Micklos
  • Hannah Little



Last checked 2017-09-11 by Alan Nielsen

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