We sought to understand (a) the mental processes underlying everyday p
redictive and postdictive judgments involving objects undergoing eithe
r change or no change of state over time and (b) the relation of these
processes to intelligence. Forty adult (nonstudent) participants were
asked to solve 40 induction problems, each presented in four forms, f
or a total of 160 test items. Half of the items involved predictions a
nd half involved postdictions; within each of these two categories, ha
lf of the items involved a state change from present to future (predic
tion) or past (postdiction), and half did not. In addition, each parti
cipant completed convergent-discriminant psychometric ability tests me
asuring inductive reasoning, deductive reasoning, and vocabulary. Pred
iction was performed more rapidly than postdiction, but was also more
susceptible to errors of judgment. Judgments involving change of stale
were more rapid and less error-prone than were judgments involving no
change. A single information-processing model was useful for describi
ng performance on both prediction and postdiction problems. A quantifi
cation of stimulus variables affecting performance via this model (wit
h six predictor variables) provided a good account of participants' re
sponse latencies. Response latencies showed convergent and discriminan
t validity, exhibiting rather high correlations with inductive reasoni
ng, but not with deductive reasoning. The paradigm we used thus seems
to provide one useful approach to understanding the relationship of ev
eryday induction to human intelligence, and to provide a complement to
the more abstract kinds of problems-such as analogies, classification
s, series completion, and matrix problems-typically seed to test induc
tive-reasoning abilities, as an aspect of intelligence.