Please help me with these two questions.

The following Minitab output is from a regression of temperature (in C} on atmospheric concentration of carbon dioxide (C02), measured in parts per million (ppm). The regression equation is Temperature = 10.5 + 0.0109 002 Predictor Coef SE Coef T P Constant 10.4831 0.6516 15.84 0.000 CO; 0.010918 0-001956 5.53 0.001 S = 0.113133 R-Sq = 79.6% Analysis of Variance Source DF SS MS E' P Regression 1 0.39861 0.39861 31.14 0.001 Residual Error 3 0.10239 0.01280 Total 9 0.50100 What are the chances of seeing a linear relationship at least as strong as observed from these data, when in fact there was none in the population? lWhat do you conclude from this regression