Top Tweets for #StatisticalClarity
To use statistics to infer whether an effect is large, we need a _prior_ specification of what "large" means. There are then 6 possible ways the CIs can play out for a single estimand (after collapsing symmetries). What are good ways to describe them? #StatisticalClarity (1/8)
#StatisticalClarity: the etymology is maybe not so clear according to @omaclaren #BIRSmath https://t.co/HwH8vCFb20
What a fantastic week @BIRS_Math in spectacular setting. Going away inspired to learn/apply new methods. Much thanks to @ruth_baker @ProfMJSimpson @DanCoombsUBC for bringing us all together!
#birsorbeers #statisticalclarity #birsmath
ASA statement on p-values: https://t.co/llNdiXuQTi #birsmath relates to #StatisticalClarity but doesn't address language per se
Slides from several #BIRSbridging talks at #BIRSmath (including two sets from me, one from the talk I promised, and one from the talk I gave launching (I hope) #StatisticalClarity. Maybe also #Checkplots https://t.co/FuCmFZUfCq
My #BIRSmath talk from #BIRSbridging is online at https://t.co/fS6y4WOLKL. The audience launched #StatisticalClarity: maybe it will go viral. @MPKain @bbolker @jakobpunkt @SACEMAdirector
A call to arms at #birsmath from Jonathan Dushoff: better language for #StatisticalClarity
Do away with
"we found no statistically significant effect,"
Instead
"we found no statistically clear effect."
Jonathan Dushoff arguing we should use #StatisticalClarity instead of statistical significance. https://t.co/zEmvKuL5ye Reminds me of the famous Camus quote !
Very interesting talk by @jd_mathbio - I can see clearly now: reinterpreting statistical significance: https://t.co/ASL4SHxEHv #StatisticalClarity #birsmath
3rd day at #birsmath and Jonathan Dushoff talks about how the language around p values and statistical significance is misleading #statisticalClarity https://t.co/BvXtpj9vLK
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