The Open Science group organizes events and workshops to offer information and training on best practices for research (open science and responsible practices).
In 2021/2022, 2022/2023, and 2023/2024, we organized together with the Doctoral Program in Psychology, several workshops on open science practices. All materials (slides and videos) are available at the OSF of the group.
We will advertise further workshops/activities organized by the group here.
Event Calendar 2024
May 22, 2024: Elaboration of Data Management Plans - hands-on workshop
Event Calendar 2023
February 15, 2023: Green Open Access
March 15, 2023: Sharing Materials and Data-bases
March 29, 2023: Study preregistration
November 23, 2023: Introduction to Data Management Plans: What it is and examples
July 07, 2023 - CPUP EVENT - Data Management Plans: Introduction and general guidelines
All events in 2021/2022
videos and materials are available in the Open Science Framework: https://osf.io/zke9h/
CPUP Event
The Open Science group organized one of the workshops of the CPUP event.
Workshop – 01/07, 9h00 às 11h00
Publishing Negative Results: Finding Evidence for the Absence of Effects with Bayesian Inference
Prof. Klaus Oberauer, University of Zurich
Summary:
In most scenarios, researchers search for positive results: interventions that promote benefits, differences between groups in a relevant measure, correlations between variables, positive predictors, or causal effects of experimental manipulations. In this search, however, we often stumble upon ineffective interventions, insignificant correlations, unsuccessful experimental manipulations, etc. These negative results are often relegated to the file drawn, often seen as a failure of the experimenter. Yet, they may inform us on variables that are not useful or findings that are not replicable or robust. Therefore, carefully documented negative results should be as much part of the scientific record as positive results. For negative results to be informative, however, we need a measure to quantify how much our data support the absence of a relation: we need tools for testing the Null hypothesis. This workshop will present the basics of Bayesian inference, and how it weights the evidence for both the Null and the Alternative hypothesis. The workshop will demonstrate how to perform some simple Bayesian-hypothesis tests (e.g., t-tests) using a free software (JASP) and how to interpret the results obtained. It will end with a discussion of the advantages of Bayesian analysis and suggestions for further references on further tests and methods.
Other pages of interest:
English 
Portuguese