Artur and Marian dissect the first published peer-reviewed Covid-19 global spread model (authored by Marian et al. back in March 2020) as an example of how different factors affect the approach to data analysis and drawing conclusions.
On the way, they discuss if it’s possible to open more emails than you receive, if pregnancy tests can be used as Covid-19 tests, and what mindset is required for an objective approach to analysis results. They discuss some controversial practices from several industries as examples of data manipulation (conscious or not) and how to avoid the most obvious pitfalls to achieve meaningful and practical results.
To read more about the Covid-19 global spread model by Marian Siwiak, Malena Siwiak, and Pawel Szczesny, you can find it here.
For some outstanding stories of people who really listen to the data, head to Who’s your data?, where the host, Gilad Barash, interviews some excellent guests with interesting data stories to tell.
And if you want to know how to tell a story with your data yourself, so others will listen, and understand, we sincerely recommend the podcast Storytelling with data
Video version of this episode is available on YouTube.
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