The Minds, Media, Machines Integrated Graduate School (MMMIGS) is hosting an online workshop about statistics for human-computer interaction. The workshop entails two session that will be held in English on the 30th of June, 14:00-18:00, and on the 2nd of July, 13:00-17:00. Participation in both session is recommended, however, it is also possible to attend only one of the sessions. Please find a detailed description of the contents below.
If you are interested in taking part in this workshop, please send an email including your name, your field of study/degree (e.g. Computer Science/PhD student) and your knowledge level in statistics to email@example.com.
The workshop entails two sessions, each of four hours or 360 minutes. The workshop is split into two sessions to allow for reflection and deeper processing. The two sessions will be offered in close sequence to maximize retention and progress. The workshop sessions will be tailored as good as possible to the level of the participants and ample opportunities to ask questions will be provided.
The two workshop sessions can be visited separately. However, we would advise most people to visit both sessions to enable a deeper familiarization with the scientific and data driven mindset underlying the workshop.
30. June 2020, 14:00 (online)
During the first session research methodology, data preparation and possibilities for visualization will be discussed and demonstrated. The quality of the planned research method has direct influence on the quality of the data that will be gathered according to it. Therefore, we will start with practical research methodology, enlarging upon the theoretical meaning and practical usefulness of such concepts as pre-registration, anchoring effect, double-blind setup and manipulation check. Vivid examples from real and fictitious research will be used to further the understanding of these concepts. In the following, aids to structure the data processing via R and Python will be specified and enriched with examples from own experiences. We will illustrate major challenges of a structured data preparation approach and – especially – their solutions. The end of the first session includes handy guidelines and examples for visualizing data in R (ggplot2) and Python (pandas).
2. July 2020, 13:00 (online)
The second session will focus on analytics. Every analysis combines certain assumptions about the data. The workshop will specifically illustrate the assumptions of ANOVA, ANCOVA, (hierarchical) regression and time series analyses and their possible assumption checks. For a set of failures of certain assumptions, possibly redeeming actions are discussed and exemplified (deviation from normality, heteroscedasticity, deviation from linearity, bottom-/ceiling effects). Each analysis procedure comprises a respective set of post-hoc analyses, which are permittable and best practice, but are – unlike assumption checks – more selectively employed. As in the first session, real and fictious examples with R and Python will enhance the active character of the workshop.