There’s this quote I love (and by “love,” I mean it makes me twitch a little every time I see it in a PowerPoint):

"There are three kind of lies: lies, damned lies, and statistics"

Now, I don’t know who actually said it—Mark Twain, Benjamin Disraeli, or your cousin who just discovered LinkedIn—but the point stands: statistics can be incredibly misleading, even when technically “true.”

I first heard that quote right after watching someone claim their product “boosted user engagement by 300%.” Cool story, bro. From what? One person to four?

When Numbers Start Acting Suspicious

We live in a data-hungry world. Businesses crave it. Marketers quote it. Startups practically bathe in it.

But here’s the catch: numbers can be bent, stretched, or dressed up in a fancy graph to tell almost any story. And if you’re not paying attention, you can end up believing some wild stuff—like thinking your email open rate is amazing because it doubled… when it went from 2 to 4 people. Congrats?

Charles Wheelan’s book Naked Statistics dives deep into this idea. It’s one of the few books about numbers that won’t put you to sleep. He lays out how stats can mislead us in subtle—and sometimes hilarious—ways.

Let’s Break This Down (No Math Degree Required)

Here are a few of the greatest hits when it comes to misleading stats:

1. The Average Trap

Say five people in a room each make $40k. Then Michael Jordon walks in. Suddenly, the average income in that room is something ridiculous like $600 million. But did anyone else get richer? Nope. Still eating frozen pizza.

Averages can hide real stories. Always ask: is that average helpful, or is it just showing off? For example, median could tell better story in this case because it doesn't get thrown off by really high or low numbers, and gives a better sense of what most people actually are.

2. Percentage Shenanigans

You’ll hear things like: “Our sign-ups grew 200%!” What they might not tell you is that they had 5 users last month and now have… 15. Is it growth? Sure. Is it world-changing? Not quite.

3. Selection Bias

This one’s sneaky. Imagine a survey that says “80% of people love our product!” But the survey was only sent to people who already bought the product and didn’t immediately ask for a refund. So… yeah, of course they like it. You didn’t ask the angry ones.

How to See Through the Number Fuzz

You don’t need to become a statistician. Just be a little nosy. Ask stuff like:

• Where could that number come from?
• What’s the actual sample size?
• Are they using percentages to hide small numbers?
• Is this average or median? (And why should I care?)

Think of it like checking the label on a smoothie. “No sugar added” sounds good—until you realize it has more natural sugar than a candy bar. Same energy.

Final Thoughts

Statistics aren’t evil. They’re just… easily manipulated. Like spreadsheets. Or toddlers.

So the next time someone drops a juicy stat to sell you something, pitch a strategy, or look smart at a meeting—take a beat. Dig a little. Odds are, there’s more to the story than what’s on the slide.

And hey, if you want to dive deeper, Naked Statistics by Charles Wheelan is actually fun. No, really. Fun. For a stats book.

Stay curious. Ask dumb questions. And don’t trust every bar chart that comes your way.