  We investigate inherent stochasticity in individual choice behavior across
diverse decisions. Each decision is modeled as a menu of actions with outcomes,
and a stochastic choice rule assigns probabilities to actions based on the
outcome profile. Outcomes can be monetary values, lotteries, or elements of an
abstract outcome space. We characterize decomposable rules: those that predict
independent choices across decisions not affecting each other. For monetary
outcomes, such rules form the one-parametric family of multinomial logit rules.
For general outcomes, there exists a universal utility function on the set of
outcomes, such that choice follows multinomial logit with respect to this
utility. The conclusions are robust to replacing strict decomposability with an
approximate version or allowing minor dependencies on the actions' labels.
Applications include choice over time, under risk, and with ambiguity.
