Coronavirus: Do You Know Your Data? (Take 2: "Enough Tests")

Every day, around the world, we keep hearing about whether we are carrying out ‘enough tests’ – but what really does this mean? To understand this, you first need to understand how sampling works. Without this, you can’t accurately read the data in front of you

Welcome back to Know Your Data – a series that helps you unpack the charts, tables and language that you’re seeing every day in relation to COVID-19 data, so you can figure out what it means for you right now.

In this second episode, Alan Schwarz and I will be focusing on the language used around testing data. We’ve seen a lot of headlines on the topic, but not many explanations about what all these terms really mean. Without that context, it is impossible to really understand the implications of what is going on, and make informed judgments about the data that’s being presented to us.

We’d like to help you answer: why is testing data important? How many tests are ‘enough’ tests? How do I know if the data I’m seeing is good news or bad?

If you want to know more or want us to cover off something you’ve seen in the media or online, do let us know via Twitter, Instagram or YouTube and include #BeDataBrilliant in your social post. Alternatively, you can email us at hello@dataliteracyproject.org

In the meantime, please stay safe!

Our own Kevin Hanegan explains how sampling works as it relates to testing for #COVID19. Read his latest blog post. #BeDataBrilliant

 

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