The Western scientific paradigm has been refined over the centuries to understand the general principles underlying observable phenomena; qualitative research focuses on describing specific instances of phenomena. As the name suggests, quantitative research is based on a foundation of counting and mathematical analysis and uses rigorous study designs, both of which seek to minimize the role of human judgment in collecting and interpreting evidence. In general, researchers use quantitative methods to look for statistical associations between variables, or for differences in patterns of health between one population and another. A fundamental motive for many (although not all) such studies is to identify causal factors that influence health status. Examples include studying patterns of risk factors between people with diabetes and those without, patterns of recovery in patients who get a treatment and those who don’t, or lifestyle patterns in different sectors of the population. Clinical trials that test the efficacy of a new therapy in curing a disease are also studies of causation: did the therapy cause the patient to recover? Because causal interpretation underlies so much of medical research, a brief description of the logic of inferring causes will be given before study designs to identify causes are described.