  Quantum decision theory (QDT) is a recently developed theory of decision
making based on the mathematics of Hilbert spaces, a framework known in physics
for its application to quantum mechanics. This framework formalizes the concept
of uncertainty and other effects that are particularly manifest in cognitive
processes, which makes it well suited for the study of decision making. QDT
describes a decision maker's choice as a stochastic event occurring with a
probability that is the sum of an objective utility factor and a subjective
attraction factor. QDT offers a prediction for the average effect of
subjectivity on decision makers, the quarter law. We examine individual and
aggregated (group) data, and find that the results are in good agreement with
the quarter law at the level of groups. At the individual level, it appears
that the quarter law could be refined in order to reflect individual
characteristics. This article revisits the formalism of QDT along a concrete
example and offers a practical guide to researchers who are interested in
applying QDT to a dataset of binary lotteries in the domain of gains.
