Authors Dipayan Biswas, (Bentley University), Guangzhi Zhao, (University of Kansas), and Donald R. Lehmann, (Columbia University) conducted four experiments to determine which type of numerical presentation elicited the greatest confidence in consumers and which led to the most accurate conclusions. They found that people have to work harder to process data presented in frequency format, which leads to higher confidence in their judgments.

Percentages appear easier for consumers to understand. The experiments showed that "when the sequential data are in percentage format, consumers tend to average the data since it is relatively easy to do so," the authors write. But averaging percentages is not always the best route to an accurate conclusion.

In contrast, when the sequential data are in frequency format, most consumers are unable or unwilling to average the data. Frequency data are just harder to mentally compute. "This occurs because most consumers are misers when it comes to cognitive processing, and averaging of sequential frequency data requires multiple mathematical operations."

"The results of our study have intriguing practical implications. For instance, when trying to discourage smoking behavior and highlighting the risks of smoking, regulators might want to use frequency format for sequential data presentation, since consumer judgment updating seems to be greater, and relatively more accurate," the authors write.

"While intuitively it might seem more prudent to present the sequential data in the seemingly more simplistic percentage format, the results of our studies show that the frequency format is more likely to lead to updated confidence judgments that are higher and also more accurate," the authors conclude.

Note: If no author is given, the source is cited instead.

• Hearing Impairment
• Consumer Behavior

• Information Technology
• Hacking

• Consumerism
• Privacy Issues

• Streaming media
• List of data structures
• Mathematical model
• Confirmation bias
• Illusion of control
• Experiment