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When you’re shopping for a fuel‑efficient car, a number like 32 miles per gallon can feel like a simple reference point. But describe that number a different way, like how many gallons it takes to get you to the airport 30 miles away, and your sense of how reliable that number is can shift, even though it’s describing the same thing.

Nicholas Reinholtz

That kind of change is the focus of new research on how people judge uncertainty.

“The big takeaway is that the way you present data changes how people understand it,” said��Nicholas Reinholtz, an assistant professor of marketing at the��Leeds School of Business and co-author of the study, published in the journal�� in December 2025.

Even when numbers describe the same situation, the way they’re presented can shape how uncertain or risky they feel, according to the researchers, who included David Zimmerman of the U.S. Securities and Exchange Commission, Stephen Spiller of the University of California Los Angeles, and Sam J. Maglio of the University of Toronto.

Bigger numbers can feel riskier

One of the clearest examples of this effect came from a simple business question: How much money will a company make? In one experiment, about 200 U.S. adults recruited online were asked to estimate a range of possible outcomes.

Some people estimated total revenue. Others estimated profit after a fixed cost was subtracted. Even though the uncertainty was the same in both cases, people judged them differently.

Participants gave much wider ranges when thinking about the bigger number, which in this case was revenue. “People act as if revenue is more uncertain than profit, even though it’s the same underlying situation,” Reinholtz said. “It’s really just because the number is larger.”

Instead of adjusting for that, he added, people rely on a simple mental shortcut: Bigger numbers feel like they should vary more, even when they don’t.

Why our intuition gets it wrong

The findings suggest that people don’t have a fixed sense of uncertainty. Instead, they build it in the moment based on what they see.

“We’ve shown examples of how you can present the same data, and people form starkly different understandings of the situation,” Reinholtz said.

For example, he said, a store might expect to sell between 30 and 40 12‑packs of soda in a day. But expressed in individual cans, that same estimate turns into a difference of 120 cans, which can feel much less certain, even though nothing about the underlying numbers has changed.

That creates a challenge in a world increasingly shaped by data, where people are encouraged to rely on numbers as an objective guide, Reinholtz said.

These effects don’t just show up in lab experiments. They can also shape real-world decisions in ways people don’t notice. A company can look more or less risky depending on whether you’re thinking about revenue or profit, even though both reflect the same underlying performance. The same goes for everyday choices, from comparing fuel efficiency to making sense of economic trends.

“We tend to assume we can present data in a neutral way that doesn’t influence decisions,” Reinholtz said. “But in practice, it’s very hard to present numbers without shaping how people interpret them.”