Humans have a well-developed ability to visually extract summary statistical information, such as understanding spatial location, the speed at which objects move, brightness levels, and so on. We make decisions based on what we see.
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Scientists at the National Center for Scientific Research in France say that other non-human primates also display some of these intuitive statistical abilities. They decided to test baboons for this purpose, which is what they described in their work on a preprint server Bio Rexiv.
Baboons understand statistics like humans.
Humans perform remarkably well at tasks that involve statistical evaluations of their environment, a skill with clear evolutionary advantages. We can estimate the probability of events arising from given distributions; recognize and learn statistical regularities in both linguistic and nonlinguistic stimuli. We can extract the average of many different features, such as color, orientation, or size, from large datasets of items—a skill set called set perception.
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It turns out we’re not the only smart apes. Chimpanzees can assess the probability of events based on available data, macaques understand simple logical relationships, capuchin monkeys can draw probabilistic inferences, and baboons can learn statistical spatial relationships.
But can they do what humans do – make collective judgments on a given data set? To find out, scientists at the National Center for Scientific Research taught a group of 23 guinea baboons (My daddy my daddy) Relate different features of scatter plots to specific geometric shapes. Their goal was to test whether baboons could judge the direction of a scatter plot. People—even children—have no problem doing this task based on the “t-values” of a data set, because they are working with a set of ordered points that increase or decrease when ordered.
It turns out that baboons were not only able to perform the same kind of intuitive statistical analysis as human adults and children – albeit with less accuracy, especially on more difficult tasks – but they did so using the same scale of T values.
The work reads:
We found that if animals are provided with easily recognizable response stimuli, they can learn the task. Their performance in the presence of noise was predicted by the t-value of the scatterplot, which is the indicator that the statistician uses to calculate the strength of association in the plot.
The new study has some interesting implications for our understanding of how the brain processes statistical information. This similar behavior, observed in both humans and baboons, suggests that the human visual system, when making direction judgments on noisy data sets, is processing evolutionarily older brain regions associated with recognizing the main focus object.
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