Effective Data Visualization in the Era of COVID-19

Free Stanford Webinar

Available on-demand

Summary

In times of crisis, such as the COVID-19 pandemic, data is critical to understanding the issues. But simply collecting data is not enough. In order to make use of data we need to be able to communicate it effectively and efficiently to a broad audience. Data visualization helps us to quickly grasp and disseminate complex information.

In this webinar, Stanford Associate Professor Kristin Sainani introduces basic concepts in data visualization, including how to graph different types of data, principles of effective data visualization, and how graphs can mislead. Dr. Sainani will also show how different visual representations of the same data can convey very different messages.

You Will Learn:

  • Principles of effective data visualization
  • How different visualizations shape our understanding of the Covid-19 pandemic
  • How graphs can inform or mislead
  • How to choose the right type of graph for your data

Presented By

Stanford Online Medical Statistics Program

Questions?

Contact us at [email protected] or 650-204-3984

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Kristin Sainani

Kristin Sainani (née Cobb) is an associate professor at Stanford University. She teaches statistics and writing; works on statistical projects in sports medicine; and writes about health, science and statistics for a range of audiences. She authored the health column Body News for Allure magazine for a decade. She is also the statistical editor for the journal Physical Medicine & Rehabilitation; and she authors a statistics column, Statistically Speaking, for this journal. She teaches the popular Massive Open Online Course (MOOC) Writing in the Sciences on Coursera. She was the recipient of the 2018 Biosciences Award for Excellence in Graduate Teaching at Stanford University.

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Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat.

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Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat.