Towards simpler and more transparent quantitative research reports

The average quantitative research report in applied linguistics is needlessly complicated. Articles with over fifty hypothesis tests are no exception, but despite such an onslaught of numbers, the patterns in the data often remain opaque to readers well-versed in quantitative methods, not to mention to colleagues, students, and non-academics without years of experience in navigating results sections. I offer five suggestions for increasing both the transparency and the simplicity of quantitative research reports: (1) round numbers, (2) draw more graphs, (3) run and report fewer significance tests, (4) report simple rather than complex analyses when they yield essentially the same results, and (5) use online appendices liberally to document secondary analyses and share code and data.