Only say “over” or “under,” or “more than” or “nearly,” with round numbers. Otherwise you just sound silly.

There are lots of correct ways to describe this data. The Journal didn’t choose any of them.

The best way to explain an abstract number? Encourage your readers to imagine something concrete and familiar.

You can’t just present two facts that sound logical together and call it causation.

When someone says “up to,” you can be pretty sure they’re the ones who are up to something.

Yes, data stories must be correct and reliable. But they have to be meaningful as well.

It’s amazing how much online “wisdom” is actually complete garbage.

When people tell you they’re making up numbers, believe them. Here are three clear indicators.

Every day I encounter data stories that are both technically correct and wildly inaccurate.

Make sure your data copy is faithful by verifying the sample and the statement.

Fast Company has featured our piece ‘Stop using data you can’t source.’

If a data source just doesn’t look right, don’t repeat it.

Lots of things used to be true. But even good data doesn’t last forever.

If you can’t find a number’s source, you cannot use it. Otherwise you’ll end up looking like a goldfish.

We know it’s obvious, but: Only use data that relates to your topic, and only make statements the data can support.

Everyone has told a data story at some point. But almost no one has been trained how. The Data Story Mandate can help.