Below is the result of running a linear regression analysis on the model posted in Part I of this series of blogs solving for global temperatures (Temp).
| R2 | 0.92 | ||||||
| Adjusted R2 | 0.78 | ||||||
| SE | 0.095 | ||||||
| Term | Coefficient | 95% CI | SE | t statistic | DF | p | |
| Intercept | -71.98 | -150.75 | to 6.79 | 34.821 | -2.07 | 9 | 0.0687 |
| Temp5 | -1.013 | -3.317 | to 1.291 | 1.0184 | -0.99 | 9 | 0.3459 |
| CO2 | 0.0813 | -0.0172 | to 0.1798 | 0.04352 | 1.87 | 9 | 0.0946 |
| Energy Cost | -0.2749 | -0.6738 | to 0.1240 | 0.17635 | -1.56 | 9 | 0.1534 |
| USP | -5.521 | -24.376 | to 13.334 | 8.3349 | -0.66 | 9 | 0.5243 |
| Energy Cons | 2.0526E-08 | -8.6206E-08 | to 1.2726E-07 | 4.7182E-008 | 0.44 | 9 | 0.6738 |
| CO2 GDP | 0.005277 | -0.006499 | to 0.017052 | 0.0052055 | 1.01 | 9 | 0.3372 |
| CO2 GDP1 | -0.0009683 | -0.0116435 | to 0.0097068 | 0.00471901 | -0.21 | 9 | 0.8420 |
| Coal KWH1 | 9.077 | -5.256 | to 23.410 | 6.3360 | 1.43 | 9 | 0.1858 |
| NG KWH1 | 2.671 | -2.250 | to 7.591 | 2.1751 | 1.23 | 9 | 0.2507 |
| Oil KWH1 | 4.071 | -3.140 | to 11.282 | 3.1878 | 1.28 | 9 | 0.2336 |
| NP KWH1 | 21.33 | -21.85 | to 64.51 | 19.088 | 1.12 | 9 | 0.2928 |
| BIO KWH1 | 2.338 | -11.152 | to 15.827 | 5.9631 | 0.39 | 9 | 0.7042 |
| Hydro KWH1 | 3.985 | -4.120 | to 12.089 | 3.5825 | 1.11 | 9 | 0.2949 |
| Geo KWH1 | -4.161 | -17.502 | to 9.180 | 5.8976 | -0.71 | 9 | 0.4983 |
| Solar KWH1 | 4.266 | -23.829 | to 32.361 | 12.4197 | 0.34 | 9 | 0.7391 |
| Wind KWH1 | 4.449 | -11.391 | to 20.289 | 7.0021 | 0.64 | 9 | 0.5410 |
| Source of variation | Sum squares | DF | Mean square | F statistic | p |
| Model | 0.964 | 16 | 0.060 | 6.64 | 0.0034 |
| Residual | 0.082 | 9 | 0.009 | ||
| Total | 1.046 | 25 |
| Coefficients | Coefficient Value | Value | Temperature | | Ave | Temperature |
| Intercept | -71.98 | 1.00E+00 | -7.20E+01 | | 1.00E+00 | -71.98 |
| Coal KWH1 | 9.077 | 1.48E+00 | 1.34E+01 | | 9.00E-01 | 8.1693 |
| NG KWH1 | 2.671 | 4.71E+00 | 1.26E+01 | | 3.10E+00 | 8.2801 |
| Oil KWH1 | 4.071 | 1.85E+00 | 7.53E+00 | | 1.15E+00 | 4.68165 |
| NP KWH1 | 21.33 | 2.30E-01 | 4.91E+00 | | 2.30E-01 | 4.9059 |
| Hydro KWH1 | 3.985 | 3.67E-01 | 1.46E+00 | | 3.67E-01 | 1.462495 |
| Geo KWH1 | -4.161 | 9.20E-02 | -3.83E-01 | | 9.20E-02 | -0.382812 |
| Solar KWh1 | 4.266 | 4.17E-02 | 1.78E-01 | | 5.00E-01 | 2.133 |
| Wind KWH1 | 4.449 | 1.43E-01 | 6.36E-01 | | 1.40E+00 | 6.2286 |
| CO2 GDP | 0.005277 | 5.10E+02 | 2.69E+00 | | 4.80E+02 | 2.53296 |
| CO2 GDP1 | -0.0009683 | 4.16E+02 | -4.03E-01 | | 3.90E+02 | -0.377637 |
| USP | -5.521 | 1.80E-01 | -9.94E-01 | | 1.60E-01 | -0.88336 |
| Energy Cost | -0.2749 | 1.00E+01 | -2.75E+00 | | 1.00E+01 | -2.749 |
| Biomass KWH1 | 2.388 | 3.21E-01 | 7.67E-01 | | 3.21E-01 | 0.766548 |
| Energy ConsP | 2.05E-08 | 9.46E+07 | 1.94E+00 | | 5.50E+07 | 1.12893 |
| CO2 | 0.0813 | 3.90E+02 | 3.17E+01 | | 4.30E+02 | 34.959 |
| Temp5 | -1.013 | 6.50E-01 | -6.58E-01 | | 7.00E-01 | -0.7091 |
| Result | | | 6.68E-01 | | | -1.833426 |
The model has excellent correlation as shown by the R² variable equal to 0.92. The results indicate that the 2009 value for global temperatures can decrease from 0.7 degrees to -1.8 degrees by decreasing the United States reliance on coal, natural gas, and oil by 25% and increasing the United States reliance on Solar and Wind energy by 25% (highlighted in red). Nuclear power, hydro power, biomass, and geothermal variables were held constant. Other 2009 variables were adjusted to keep up with the trends of using renewable energies such as increased energy costs, higher global temperatures (Temp5 – even with lower CO2 emissions the global temperature trend is upward), lower energy consumption (including the USP variable), and lower CO2 to GDP numbers.
Global warming alarmist may look at this as proof that moving to renewable energy sources will eliminate CO2 and therefore; reduce global temperatures. This, however, is not true and this result can be misleading as will be revealed in future blog posts evaluating this model.
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