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Speaker:
Nina Ehmann, Dr. Alan Novaes Tump, Prof. Eric-Jan Wagenmakers

This event is part of an event series „Bayesian Lecture Series“.

We are excited to announce a new talk series at the Psychology department: “An Alternative Perspective on Statistics: Exploring Bayesian Data Analysis” – organized by Nina Ehmann and with support of MIDPSY (Methods for Intensive Data in Psychology at the University of Konstanz).

This series aims to introduce Bayesian statistics from the very beginning, and offers insights into applications in research from various perspectives. It is designed for both students and researchers from the Psychology department and beyond who are new or completely new to Bayesian statistics. 

For any inquiries or feedback, kindly reach out to Nina Ehmann.

Our current schedule (see below for more details):

• Monday, July 8th, 03:15 pm – Kick-Off Talk “Beyond P-Values: A Basic Introduction to Bayesian Statistics“ by Nina Ehmann (University of Konstanz).
• Wednesday, July 10th, 05:00 pm – “Bayesian Computational Modelling of Collective Behaviour with the Drift-Diffusion Model” by Dr. Alan Novaes Tump (Max Planck Institute for Human Development, Berlin).
• Tuesday, July 23rd, 04:00 pm – "The Bayes factor hypothesis test: Its inevitability, its advantages, its elegance, and the epistemic perils that await those who spurn it". Talk by Prof. Eric-Jan Wagenmakers (University of Amsterdam).
• Other talks may follow.

All talks will be held via Zoom: 
https://uni-konstanz-de.zoom.us/j/5379783910?pwd=SC9HcENFUzA1SEZBVy9YRldwclRjUT09

Meeting ID: 5379783910

Monday, July 8th, 03:15 pm, Kick-Off Talk:

Beyond P-Values: A Basic Introduction to Bayesian Statistics (Nina Ehmann, Universität Konstanz)

Have you ever wondered if there is a more intuitive way to analyze psychological data than just looking at traditional p-values? In this introductory talk, we will look at the basics of Bayesian statistics – a versatile approach that allows us to combine prior knowledge with new data, while updating our current knowledge continuously. Along practical examples, we will explore how Bayesian updating works and how it differs from classical statistics. We will look at both advantages and disadvantages and there will be room for your questions and discussion points. Everyone should feel very welcome to join, no prior knowledge is needed!

Wednesday, July 10th, 05:00 pm:

Bayesian Computational Modelling of Collective Behaviour with the Drift-Diffusion Model. (Dr. Alan Novaes Tump, Max Planck Institute for Human Development, Berlin)

Collective dynamics play a crucial role in everyday decision making. Whether social influence promotes the spread of accurate information and ultimately leads to collective intelligence, or whether it leads to false information cascades and maladaptive social contagion, depends on the cognitive mechanisms underlying social interactions. In my talk, I will show how computational modelling of cognition allows us to better understand such collective dynamics. I will begin with a brief general introduction to computational models of cognition and the drift-diffusion model (DDM). I will then illustrate the synergy between Bayesian statistics and cognitive modelling, and show how a social version of the DDM allows us to uncover the strategies underlying decision making and information flow in groups, and why these strategies often allow groups to benefit from social information exchange and why they sometimes fail.

Tuesday, July 23rd, 04:00 pm: 

Talk by Prof. Eric-Jan Wagenmakers (University of Amsterdam)

TBD

We are looking forward to welcoming you in any of the talks.

https://uni-konstanz-de.zoom.us/j/5379783910?pwd=SC9HcENFUzA1SEZBVy9YRldwclRjUT09

Please note: The introductory talk from last Monday on the basics of Bayesian statistics has been recorded. Upon your request, Nina Ehmann can provide you with the link.