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Appreciating Statistics

📄 Original study
Utts, Jessica 2016 Current Era overview

Plain English Summary

In a rare mainstream moment, the president of the American Statistical Association used her keynote to discuss why good data gets ignored -- and yes, she went there with psychic research. Drawing on Kahneman's framework of mental shortcuts (fast gut-feeling versus slow careful thinking), she showed even trained scientists botch statistics: nearly 90% of research psychologists misjudge how much data they need. Having worked on the CIA's remote viewing program, she knew the psychic data were statistically strong yet dismissed without a glance. Her fix is wonderfully human: pair numbers with compelling stories, because data alone rarely changes minds.

Research Notes

Rare mainstream endorsement of psi data quality from a sitting ASA president in the field's top journal. Illustrates the meta-debate about why strong statistical evidence fails to convince when findings conflict with prior beliefs. Kahneman's cognitive bias framework offers a theoretical account of scientific resistance to psi.

Presidential address exploring the rapid growth of statistics as a profession (AP exam: 7,667 to 207,876 test-takers, 1997–2016; 34% projected job growth) alongside the challenge of making statistical thinking accessible. Using Kahneman's System 1/System 2 framework, argues that intuitive cognition creates systematic barriers to statistical reasoning 89% of research psychologists overestimate small-sample power; 95% underestimate needed sample sizes. From experience with the CIA's 20-year remote viewing program, notes psi data are "quite strong statistically" yet rejected without examination. Proposes "data plus stories" over "data beat anecdotes" as a communication framework.

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📋 Cite this paper
APA
Utts, Jessica (2016). Appreciating Statistics. Journal of the American Statistical Association. https://doi.org/10.1080/01621459.2016.1250592
BibTeX
@article{utts_2016_appreciating,
  title = {Appreciating Statistics},
  author = {Utts, Jessica},
  year = {2016},
  journal = {Journal of the American Statistical Association},
  doi = {10.1080/01621459.2016.1250592},
}