We study cooperative and sequential decision making in a population of individuals each implementing the sequential probability ratio test.  The individual decisions are combined into a collective decision via an aggregation rule.  For distinct aggregation rules and interaction protocols, we study how the population size affects the performance of the collective decision making, i.e., the decision accuracy and time.  Our results are related to previous work by Varshney '96 and Veeravalli, Basar & Poor '93 on the design of optimal strategies.  We analyze three aggregation rules. In the first rule, the group decision is equal to the first decision made by any individual. In the second rule, the group decision is equal to the majority of the decisions. In the third rule, a pre-selected leader decides for the group.  Regarding communication protocols, the individuals either do not exchange information or exchange information according to a message passing protocol.  Under the assumption of measurement independence among individuals, we introduce a novel numerical representation of the performance of cooperative decision making.  Our analytical and numerical results characterize the tradeoff between accuracy and decision time as a function of the population size for various combinations of aggregation rules and interaction protocols.