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As an epidemiologist, I am interested in disease - and more specifically, who in a population currently has or might get that disease. What is their age, sex, or socioeconomic status? Where do they live? What can people do to limit their chances of getting sick? Questions exploring whether something is likely to happen or not can be answered with quantitative research. By counting and measuring, we quantify (measure) a phenomenon in our world, and present the results through percentages and averages. We use statistics to help interpret the significance of the results. While this approach is very important, it can't tell us everything about a disease and peoples' experiences of it. That's where qualitative data becomes important.

In 1967, following riots in Detroit, Philip Meyer used survey research methods, powered by a computer, to show that college-educated people were just as likely to have rioted as high school drop outs. His story was one of the first examples of computer assisted reporting and precision journalism, in which journalists use social science methodologies to extract and tell stories. In recognition of his contribution to the area, each year's best computer-driven and precision stories are celebrated through the Philip Meyer Journalism Award. The Award's 2016 winners have just been announced, with the successful entries showcasing techniques derived from quantitative and qualitative methods, such as surveys using randomly-selected respondents, descriptive and inferential statistical analysis, social network analysis, content analysis, field experiments, and more.