The field of data visualization is the intersection of data journalism, statistics, graphic design, computer science, neuroscience, and cognitive psychology. We will focus on the latter two fields of data visualization as it relates to data visualization: neuroscience and cognitive psychology.
Date: Wednesday 28th April 2021
Time: 16:00 - 17:00 GMT
Speakers: Zachary Skrivanek, (Lilly)
Who is this event intended for? This event is intended for all statisticians and statistical programmers interested in data visualization. The webinars will cover visualizations to explore and to communicate data. Those submitting data visualizations themselves, which are based on the provided data sets, will benefit mostly from the webinars.
What is the benefit of attending? The participants will learn about usual challenges for data visualization based on real-life examples from the healthcare industry. Instead of working on generic data, you’ll have the opportunity to improve your visualization skills for data from clinical trials, real world evidence and similar data sources. You’ll mostly benefit from the webinar, if you have submitted a data visualization yourself. The continued attendance of the webinar series will improve your data visualization skills as each visualization design has its own aspects.
You can now register for this event. This event is free of charge to both Members and Non-Members of PSI.
To register for the session, please click here.
The field of data visualization is the intersection of data journalism, statistics, graphic design, computer science, neuroscience, and cognitive psychology. We will focus on the latter two fields of data visualization as it relates to data visualization: neuroscience and cognitive psychology. In neuroscience, scientists have demonstrated that the visual cortex can recognize certain types of patterns within 250 milliseconds; this is called pre-attentive processing. We will illustrate these concepts through an empirical experiment with the audience. We will cover what types of patterns are conducive to pre-attentive processing and how to incorporate these concepts in your data visualizations. Similarly, in cognitive psychology, the study of gestalt principles, seeing meaning in a purposeful arrangement of design elements, can be leveraged for effective data visualizations; it has even more applications in designing an effective user interface which should be taken into account when creating an interactive data visualization. We will also discuss the hierarchies of perception and how this applies to data visualization.
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Dr. Skrivanek graduated with a Ph.D. in biostatistics from Ohio State University and a B.S. from Cornell University, where he studied exploratory data analysis under Professor Velleman, a protégé of John W. Tukey, who invented a number of statistical graphics including the box plot. He joined Eli Lilly in 2002 where he contributed to the development of endocrine-related medicines and related biomarkers in early clinical phase drug development. He later transitioned to a product team in late phase clinical development as the lead statistician and developed and successfully implemented an innovative Bayesian adaptive, seamless phase 2/3 study which selected the doses for the entire program utilizing a clinical utility index. Dr. Skrivanek heavily leveraged data visualization to communicate the operating characteristics of the design as well as the results of the study. He is currently leading an effort to make visual analytics and good data visualization practices in general an integral part of drug development at Eli Lilly and the industry in general. He is involved in a number of external collaborations focused on advancing drug development through visual analytics including co-leading a subproject in PHUSE, on “Interactive Data Visualizations for Decision Making in Submissions”, and contributing to an ASA-DIA working group on interactive safety graphics and an organizing member on a PSI (Statistics in the Pharmaceutical Industry) Special Interest Group (SIG) which hosts a monthly event, “Wonderful Wednesdays” where members are given data visualization challenges that they must solve for the following month and the solutions are critiqued by the panel based on good data visualization principles.
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