statisticrather

Statisticrather is a neologism used in some data-literacy and statistics discussions to describe a methodological stance that prioritizes statistical reasoning in the interpretation of data. It characterizes approaches that emphasize quantitative evidence and uncertainty over purely narrative or qualitative explanations. The term is not part of formal statistical theory but appears in blogs, commentary, and teaching materials as a way to discuss methodological preferences within a broader culture of data analysis.

Etymology and origin: The word blends statistics with rather, signaling a preference for statistical evidence. It emerged in informal online discourse in the mid-2010s and has since circulated mainly in educational and practitioner communities rather than in peer-reviewed journals.

Practice and scope: A statisticrather stance tends to promote practices such as reporting effect sizes and confidence intervals, focusing on model uncertainty, preregistration, replication, and transparent reporting of methods. It often aligns with efforts to move beyond sole reliance on p-values and to incorporate Bayesian perspectives, robustness checks, and sensitivity analyses. In teaching and science communication, statisticrather is used to advocate for disciplined data interpretation that respects variability and limitations.

Criticism and limits: Critics argue that the term is vague and may conflate multiple, distinct methodological ideals under a single label. Some worry that it risks undervaluing substantive theory, context, or qualitative insight in mixed-method research. Proponents respond that it simply emphasizes rigorous statistical thinking as a default.

See also: statistics, data science, evidence-based practice, preregistration.