Complex Human Data Summer School

summer school logo

Dates: December 15 - 20, 2019

Applications are now closed (as of October 15th, 2019)

Venue: All sessions will be held in rooms 110 and 111 of the Stop 1 building on campus at the University of Melbourne.


Summary: Researchers from psychology and other disciplines are increasingly relying on computational analyses of large data sets to draw conclusions about human behaviour. This kind of research requires skills that are not often taught as part of the psychology curriculum. Last year we launched a summer school to help people collect and analyse complex human data, and we are running a second iteration of the school this December.  The school is designed for advanced undergraduates, PhD students, and industry participants. The goal is to give attendees the key skills they need to collect complex data, model the data, and evaluate their models.  The program interleaves lectures and laptop-based sessions which provide hands-on experience of the computational tools and approaches to be covered. 

Topics will include: 
- Programming in R (the main language for the summer school)
- Best practices for running online studies
- Reproducibility and Open Science 
- GitHub
- Exploratory data analysis

along with other topics such as:
- Bayesian data analysis
- Probabilistic models of cognition
- Experience sampling

More information about last year's content is at:

This year's content will be slightly different, but the overlap with last year's summer school will be substantial. Except in unusual cases, participants from last year should not apply again this year.

Organisers: Simon Dennis, Charles Kemp, Danielle Navarro, Amy Perfors

Required background: Participants are expected to have an interest in psychology and some experience with computer programming. The school is designed both for psychologists with an interest in computational approaches and computer scientists (or people from another technical discipline) with an interest in psychology. Although we expect that many participants will have earned or will be working towards a postgraduate degree, a subset of the available slots will be reserved for advanced undergraduates. 

Cost: Registration is free for undergraduates and graduate students, and $2500 for industry participants. Participants not from Melbourne can apply for a scholarship of up to $500 to help defray transport and accommodation costs.  Last year a number of participants arranged funding from their home institutions and we encourage you to explore this option. International students are welcome to apply, but scholarships for international participants are capped at $AUD 500.

  • Sunday, Dec 15: R Bootcamp
    • 1 - 4:30. Afternoon session
  • Monday, Dec 16: Folder design & Workflow, GitHub, Google App Engine
    • 9:30 - 12:00. Morning session
    • 12:00 - 1:00. Lunch break
    • 1:00 - 4:30. Afternoon session
    • 4:30 - Group photo and reception
  • Tuesday, Dec 17: Introduction to Tidyverse, Data wrangling, Exploratory data analysis and visualization
    • 9:30 - 12:00. Morning session
    • 12:00 - 1:00. Lunch break
    • 1:00 - 4:30. Afternoon session
  • Wednesday, Dec 18: Online Experiments
    • 9:30 - 12:00. Morning session
    • 12:00 - 1:00. Lunch break
    • 1:00 - 4:30. Afternoon session
  • Thursday, Dec 19: Advanced Tidyverse, Statistics
    • 9:30 - 12:00. Morning session
    • 12:00 - 1:00. Lunch break
    • 1:00 - 4:30. Afternoon session
  • Friday, Dec 20: Case studies, Closing Panel
    • 9:30 - 1:00. Morning session

For more information: Please contact Charles Kemp (