From: f00@0f0.00f   
      
   Dawn Flood wrote:   
   > Last year I committed to providing this group with annual updates   
   > on worldwide temperature anomalies versus annual CO2   
   > concentrations, and so, here is my January 2026 update for this   
   > past year.  First off, my data sources; for the annual   
   > temperature anomalies, go here:   
   >   
   > https://data.giss.nasa.gov/gistemp/tabledata_v4/GLB.Ts+dSST.txt   
   >   
   > This is from a NASA GISS website, and I am pulling the J-D values   
   > for each year.  For CO2 concentrations, here is the NOAA website:   
   >   
   > https://gml.noaa.gov/webdata/ccgg/trends/co2/co2_annmean_mlo.txt   
   >   
   > As before, it's the annual concentration.  I am using Minitab   
   > v14, and ran a regression with the dependent variable being   
   > temperature anomalies and the independent being CO2   
   > concentration; here are the results:   
   >   
   > —————   1/14/2026 2:05:41 PM   —————†  
   â€”—————————————   
   >   
   > Worksheet size: 10000 cells.   
   >   
   > Welcome to Minitab, press F1 for help.   
   > Retrieving project from file: 'C:\Program Files (x86)\MINITAB 14   
   > Student\Studnt14\Global Warming.MPJ'   
   > MTB > Regress 'Temp' 1 'CO2';   
   > SUBC>   Constant;   
   > SUBC>   Brief 2.   
   >   
   > Regression Analysis: Temp versus CO2   
   >   
   > 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   
   >   
   > As compared to the 2024 results, the R-Sq has gone up from 93.1   
   > to 93.5 (with a corresponding smaller T-value); the tool is still   
   > identifying #66 (2024) as being an outlier.   
   >   
   > Dawn   
      
   2024 had some el nino thing?   
      
   --- SoupGate-Win32 v1.05   
    * Origin: you cannot sedate... all the things you hate (1:229/2)