Don’t Average Averages

Or percentages, for that matter.

If there’s just one thing we could tattoo on the forehead of every data enthusiast (metaphorically, of course), it’s this: never average averages – or percentages. Seriously, just don’t.

We’ve seen it happen at massive corporations and in high-stakes strategic reports. C-level decisions being made on flawed numbers, all because of this sneaky little misconception. Here’s the deal: averaging averages ignores the different sample sizes or weights behind each number. Sure, if your data is perfectly stable, it might seem close enough but when there’s variation or big differences in group sizes? You’re headed straight for misleading results.

A quick example to bring it home:
You’ve got 100 boys and 30 girls. Of the boys, 70% love chocolate (because of course they do), but only 20% of the girls share that passion. If you average the percentages directly, you’d get (70% + 20%) / 2 = 45%. Sounds reasonable, right? Except it’s wrong.

When you factor in the actual group sizes, the correct calculation is: (70 boys + 6 girls) / 130 kids = 58%. That’s a huge difference, driven by the larger group of chocolate-loving boys.

And that’s the gist! Want to dive deeper into why this matters and how it plays out in real-world scenarios? We’re all ears, and calculators. Drop us a line, and let’s geek out together.