Making predictions always presents a risk. Whether it be monetary or pride-induced, people strive to boost their chances of winning. A study done by Dr. Aaron Brough, assistant professor at the Jon M. Huntsman School of Business at Utah State University, and Dr. Matthew Isaac, assistant professor at the Albers School of Business and Economics at Seattle University, illustrates that groupings can affect how people make their predictions.
Their research began as all do, with a question. For their particular study they wanted to know why people make bad predictions. Specifically, they wanted to understand why categorization can influence decision making.
Brough explained, “We had a hypothesis that when you take a possible outcome and group it with a lot of other possible outcomes, that all of a sudden it seems more likely to occur.”
To test their hypothesis, they divided their research into five tests comprised of around 700 participants total. Each test either revolved around a game of chance (lottery), games of skill (sporting events), and assessment of risk (security threats).
In one particular test, they gave lottery tickets to individuals that were either on yellow or blue paper. Overall, most of the lottery tickets were printed on blue paper. When told more lottery tickets were on blue, participants with the blue lottery cards believed they were more likely to win. Consequently, once they understood that blue lottery cards were the majority, individuals wagered 25 percent more than they originally would have.
Another test took place during the college basketball season. Participants were asked to group school mascots by similarities. They were then asked to estimate the odds of either Florida State University winning or University of Wisconsin winning based on mascot groupings. No matter how participants’ grouped the mascots, one of these universities would be in a smaller group than the other. The team individuals’ predicted to be more likely to win was usually in the larger group.
This, along with the other tests’ findings, supported both the hypothesis and a statistical term: category size bias. Brough explained that the findings of the study could have wide ranging implications.
“[By] controlling the way to present information in an advertising message, I could encourage people to take better care of their health. So for instance, if I present health risks and I present a particular type of cancer in a group of a lot of other types of cancer, the fact that it is part of a large group could make it seem more likely [to happen] which could encourage me to go to my doctor and get a screening of that type of cancer,” Brough said.
He further explained that this finding can also help people make better predictions by realizing the psychological impact size makes on these decisions.
“Knowing we can contribute to a greater understanding of how people’s decision-making process works, that is kind of what I am always trying to do in my research is to figure out: What are people thinking?” Brough explained. “I am trying to get into their heads, and I am trying to understand what is leading them to engage in these behaviors and make these decisions. And so if I can identify behaviors, or decisions that are clearly irrational and then help explain why they might be doing that, to me that is satisfying because it helps us understand humans better.”
The full study can be found in the <em>Journal of Consumer Research</em>.