Replicated experiments at the level of the population are often not feasible for field systems. Despite this, population-level observational studies play a critical role in biology. For example, they have revealed how environmental change generates ecological and evolutionary change in free-living populations. When replicated experiments are impossible, constructing models and using these to conduct in silico experiments is the next best thing. Recent advances in the construction and analysis of integral projection models (IPMs) mean they offer a remarkably powerful tool to study ecological and evolutionary dynamics. IPMs can be parameterised using data frequently collected by ecologists, but the ease with which they can be constructed and analysed is perhaps not as widely appreciated as it could be. In this paper, which is loosely related to the talk I gave when receiving the Per Brinck Oikos Award in 2012, I show how easily IPMs can be constructed and analysed, and I argue they play an important role in posing and testing hypotheses in population biology.