When you selected the college or university you planned to attend, how did you do it? Did you read narratives offered by college guides? Did you compare relevant statistics such as the student/teacher ratio and percent of students who went on to graduate school? Did you listen to the advice of older friends who had attended the school? Or did you visit the school in person? And which of these factors had the most impact on your decision?
For many students, the campus visit is the deal-maker (or breaker). Here at Davidson I’ve met many students who said they had been undecided, but when they visited the campus, they “fell in love.” I’ve also met students who regretted their decision to come here. And, no doubt, there have been students who visited campus on a rainy day, attended a boring lecture, and found the Davidson students unwelcoming and uninspired, and so went elsewhere. Were they giving proper weight to the campus visit in making their decisions?
Many studies have addressed how people make important decisions like which college to attend, but one of the classics was conducted way back in the 1980s, by a team led by Richard Nisbett. Even at this time, psychologists knew that people often make decisions that aren’t supported by seemingly obvious evidence. In the 1970s, Daniel Kahneman and Amos Tversky had asked people which of two hospitals was more likely to have a day with at least 60% male babies born, a hospital with 15 births per day, or one with 45 births per day. Most people said that the chances were the same in each hospital, but in fact there should be more variance in the male-female ratio in the smaller hospital, which means it would have more 60-percent days.
But do people really just not understand the statistics behind such a prediction, or do they not think to apply what they know? Nisbett’s team asked 46 students to imagine they were an explorer who had landed on a remote South Pacific island. There they found a variety of things, including a new species of bird, a “shreeble,” which was blue, and a native man, a member of the Barratos tribe, who was obese. Then they were asked what portion of all shreebles were blue, all Barratos were obese, and so on, for several different novel things found on the island. These questions were repeated for varying numbers of cases seen, like if they had seen 3 shreebles, all blue, or 20 Barratos, all obese. Here are some of the results:

For shreebles, the respondents assumed that one bird is a pretty good representation of the whole population. But one obese Barratos was not taken to be convincing evidence that all Barratos are obese. As the number of obese examples increases, so does the estimate of what portion of the entire population is obese. This is entirely in keeping with statistical logic (of course, there are other possible explanations: perhaps obese Barratos just have more trouble hiding from strange intruders on huge ships).
So if it’s true that college students can use statistical reasoning in some cases, what determines whether they’ll use it? In a new experiment, 157 students were given one of two scenarios describing one student’s experiences deciding which of two colleges to attend.
In both scenarios, “Daniel” had been accepted at both Ivy U. and Liberal College, and several of his older friends were attending each. The friends at Ivy U. said they had many complaints about the education, personal, and social life there, while the friends at Liberal College said everything was great. Daniel decided to visit each campus for a day, and had a terrible time at Liberal College and a great time at Ivy U.
But the second scenario added a critical detail:
Before his visit, Daniel proceeded systematically to draw up a long list, for both colleges, of all the classes which might interest him and all the places and activities on campus that he wanted to see. From each list, he randomly selected several classes and activities to visit, and several spots to look at (by blindly dropping a pencil on each list of alternatives and seeing where the point landed).
When this detail was omitted, 74 percent of students in the study said Daniel should go to Ivy U., which his friends didn’t like, but where he had a good time for a day. When it was included, only 56 percent of respondents said he should go to Ivy U. — a significant difference. The researchers say the reason for the difference is that the second group had been led by the extra detail to think about the problem using statistical reasoning: his friends had been at each school much longer than he had, so their experience should probably carry more weight than his own brief visit.
In another experiment, they found that experienced athletes and actors were more likely to say a great try-out didn’t necessarily imply a long-lasting talent in their respective activities (compared to non-athletes and actors), because they understood that it’s statistically possible to have a single good try-out, which isn’t necessarily representative of day-in, day-out ability.
Overall, the researchers found that a predisposition to look at data statistically (either because of hint given by the experimenters, the nature of the data, or the nature of the individual’s experience) led to more statistical reasoning. In addition, people who had been trained in statistics — both formally and informally in very brief training sessions — were more likely to use statistical reasoning to solve problems.
Nisbett’s team understood that statistical reasoning isn’t the only relevant way to make decisions. In Daniel’s case, he simply may have been better suited for Ivy U. than Liberal College, despite the experiences of his friends — but it would be wrong to consider only his own brief experience in recommending what he should do.
Unfortunately, a quick look across the news pages reveals that statistical reasoning hasn’t improved since 1983, and may even have declined: witness the widespread acceptance of pseudoscience like homeopathy, anti-vaccination, anti-global warming, and anti-evolution thinking. And college admissions offices will tell you that getting prospective students to visit campus is a key way to ensure they actually attend.
Nisbett, R.E., Krantz, D.H., Jepson, C., & Kunda, Z (1983). The use of statistical heuristics in everyday inductive reasoning Psychological Review, 90 (4), 339-363