I introduce some epidemiologic principles and context and describe how epidemiologists employ different kinds of inference to move from a study sample as a reflection of what is going on in the underlying population to intervention. In a study sample they collect data, create estimates, use these as evidence, to generate causal knowledge, which helps justify interventions (transitional inference). Related kinds of inference include the inference from association to causation, from animal experiment to human application, from population to individual, and from research setting to real world (translational inference).