Frequency, probability, and prediction: Easy solutions to cognitive illusions?

Many errors in probabilistic judgment have been attributed to people's inab ility to think in statistical terms when faced with information about a sin gle case. Prior theoretical analyses and empirical results imply that the e rrors associated with cases-specific reasoning may be reduced when people m ake frequentistic predictions about a set of cases. In studies of three pre viously identified cognitive biases, we find that frequency-based predictio ns are different from-but no better than-case-specific judgments of probabi lity. First, in studies of the "planning fallacy," we compare the accuracy of aggregate frequency and case-specific probability judgments in predictio ns of students' real-life projects. When aggregate and single-case predicti ons are collected from different respondents, there is little difference be tween the two: Both are overly optimistic and show little predictive validi ty. However, in within-subject comparisons, the aggregate judgments are sig nificantly more conservative than the single-case predictions, though still optimistically biased. Results from studies of overconfidence in general k nowledge and base rate neglect in categorical prediction underline a genera l conclusion. Frequentistic predictions made for sets of events are no more statistically sophisticated, nor more accurate, than predictions made for individual events using subjective probability. (C) 1999 Academic Press.