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# Writing about P-values in science journalism, for National Association of Science Writers conference

Practical, applied advice for understanding and writing about statistics in science journalism.
Published on: Mar 3, 2016
Published in: Education

#### Transcripts - Writing about P-values in science journalism, for National Association of Science Writers conference

• 1. Writing about P-values in science journalism Regina Nuzzo, Ph.D. Freelance Science Writer Statistics Professor, Gallaudet University @ReginaNuzzo Rnuzzo@gmail.com National Association of Science Writers Columbus, Ohio October 18, 2014
• 2. I can’t even. Writing about P-values in science journalism:
• 3. P-values are the hurdle to publication – and thus media attention. They’re worth understanding.
• 4. P-values: A bad romance. P-values can never satisfy our needs, but we keep coming back to them.
• 5. What do the statistics mean? What does the result imply? How plausible is the conclusion? How newsworthy is the study? P-values: A bad romance. P-values can never satisfy our needs, but we keep coming back to them. Science writers’ needs:
• 6. “What does the P-value really mean?” “We are 95% confident that the effect is true.” “There is a 5% chance that the findings are due to chance.”
• 7. “. . . the mathematic probability of his findings being a statistical fluke are one in 74 billion.”
• 8. “. . . the mathematic probability of his findings being a statistical fluke are one in 74 billion.” “. . . there was a 3.9% probability that chance accounted for the difference.”
• 9. “. . . the mathematic probability of his findings being a statistical fluke are one in 74 billion.” “. . . there was a 3.9% probability that chance accounted for the difference.” “ . . it has just a 0.00003% probability that the result is due to chance.”
• 10. “. . . the mathematic probability of his findings being a statistical fluke are one in 74 billion.” “. . . there was a 3.9% probability that chance accounted for the difference.” “ . . it has just a 0.00003% probability that the result is due to chance.” “By convention, a p-value higher than 0.05 usually indicates that the results of the study, however good or bad, were probably due only to chance.”
• 11. “. . . the mathematic probability of his findings being a statistical fluke are one in 74 billion.” “. . . there was a 3.9% probability that chance accounted for the difference.” “ . . it has just a 0.00003% probability that the result is due to chance.” “By convention, a p-value higher than 0.05 usually indicates that the results of the study, however good or bad, were probably due only to chance.”
• 12. “On the plus side, if a newspaper column runs 20 times, I guess it’s ok for it to be wrong once— we still have 95% confidence in it, right?” Andrew Gelman Professor of Statistics Columbia University http://andrewgelman.com
• 13. “By convention, a p-value higher than 0.05 usually indicates that the results of the study, however good or bad, were not reliably different enough from random chance.” “A p-value indicates how unusual a result would be, if it were only a chance occurrence.” “By convention, journal editors reject papers unless they report a p-value less than 0.05.” “The finding was fairly inconsistent with random chance.”
• 14. “What does the result imply?” Size matters. 1. Report the actual effect. 2. Probe researchers. Ask: “What is the effect size?” “What is the confidence interval?” “What is the R-squared?” *
• 15. * R-squared is surprisingly easy. “ . . . by Nature's calculation the split-second attitudes explained only about 2% of the differences in people’s happiness” “ . . . this effect remained significant controlling for all covariates [B = 0.14, SE = 0.06, t(232) = 2.15, P = 0.032; effect size r = 0.14].” 0.14 * 0.14 = 0.0196 = 1.96%
• 16. “How plausible is the conclusion?” “Extraordinary claims require extraordinary evidence.” Ask: “How plausible was the hypothesis in the first place?” “What other evidence supports this?” “Putting the data aside, did you have a prior reason to think this would be important?’
• 17. P-values are not always strong evidence. Nuzzo, R. Scientific method: statistical errors. Nature 2014, 506:150–152. 13.
• 18. “How news-worthy is the study?” Use your judgment: Did they set out to study this – or did they just stumble upon the finding? Did they cherry pick their results – or did they disclose all their findings and methods? Was this “exploratory” or “validating”?
• 19. P-Hacking: Lots of p-values in the tables – but only a few barely below 0.05. Abstract talks about an incidental finding – but ignores what they set out to study in the first place. “Exploiting -- perhaps unconsciously -- researcher degrees of freedom until p<.05.”
• 20. Help on the Horizon Science Journalists!
• 21. Prob(your attention is appreciated) > 0 Thank you!
• 22. References: http://www.dailytelegraph.com.au/proof-we-all-have-psychic-powers/story-e6freuy9-1225955980141 http://online.wsj.com/articles/SB125511780864976689 http://www.nature.com/news/physicists-find-new-particle-but-is-it-the-higgs-1.10932 http://www.nytimes.com/2013/03/12/science/putting-a-value-to-real-in-medical-research.html http://andrewgelman.com/2013/03/12/misunderstanding-the-p-value/ http://www.nature.com/news/newlyweds-gut-feelings-predict-marital-happiness-1.14261 http://www.nature.com/news/scientific-method-statistical-errors-1.14700 http://www.urbandictionary.com/define.php?term=p-hacking Image Credits: http://atlantis.haktanir.org/ch3.html http://home.nordnet.fr/~scharlet/histoire/DetroitAthleticClub.htm http://commons.wikimedia.org/wiki/File:Explosions.jpg http://wellcomeimages.org/indexplus/image/V0030067.html http://commons.wikimedia.org/wiki/File:Lou_Grant_Ed_Asner_1977.JPG http://hellcorpceo.deviantart.com/art/A-lovely-unicorn-197967762 http://pixabay.com/en/firefighter-fire-helmet-rescue-23755/