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|    Message 95,540 of 95,770    |
|    Dawn Flood to Paul Aubrin    |
|    Re: If predictions fail your hypothesis     |
|    27 Jan 26 12:48:46    |
      XPost: alt.global-warming, alt.atheism, alt.messianic       From: Dawn.Belle.Flood@gmail.com              On 1/27/2026 12:17 PM, Paul Aubrin wrote:       > Le 27/01/2026 à 14:30, Dawn Flood a écrit :       >> On 1/27/2026 12:16 AM, Paul Aubrin wrote:       >>> Le 27/01/2026 à 01:23, Dawn Flood a écrit :       >>>>> To day I danced a rain dance. If it rains tomorrow, how would you       >>>>> explain that ?       >>>>>       >>>>       >>>> Only if your predictions can constitute a statistically significant       >>>> result       >>>       >>> That is not enough. One single erroneous prediction can invalidate a       >>> false hypothesis. But you need many good predictions, all over the       >>> validity domain, to gain confidence in a new hypothesis.       >>> All the climate models failed the comparison with observations over       >>> the 1979 to 2016 periodd.       >>>       >>       >> They also fail over the 2016-2017 period, as well as this past       >> weekend. Try extending your graph instead of cropping it.       >       > 1) the comparison with reality (observation) became statistically       > significant in 2016.       > 2016-1979 = 37 years, that is more than the 30 years which define       > "climate".       > 2) A single counter-example is enough to invalidate a general hypothesis       > of physics.              As I posted already, here is the regression equation that I get using       the NASA GISS & the Mauna Loa CO2 observatory:              Regression Analysis: Temp versus CO2 (1959 -- 2025)              The regression equation is       Temp = - 351 + 1.08 CO2                     Predictor Coef SE Coef T P       Constant -350.57 12.77 -27.46 0.000       CO2 1.08012 0.03519 30.69 0.000                     S = 9.40662 R-Sq = 93.5% R-Sq(adj) = 93.4%                     Analysis of Variance              Source DF SS MS F P       Regression 1 83344 83344 941.91 0.000       Residual Error 65 5751 88       Total 66 89096                     Unusual Observations              Obs CO2 Temp Fit SE Fit Residual St Resid        66 425 128.00 108.06 2.51 19.94 2.20R              R denotes an observation with a large standardized residual.              END OUTPUT              Ditch all the climate models if you wish, and run the regression for       yourself.              Dawn              --- SoupGate-Win32 v1.05        * Origin: you cannot sedate... all the things you hate (1:229/2)    |
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