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CO2islife concludes: ‘If you have to “adjust” the data to make your model work, your model is wrong, it is that simple.’

In any real science great care is given to “controlling” for exogenous factors. The whole purpose of the scientific method is to relate the impact of an independent variable upon a dependent variable, removed from any other factors. Y = mX + b + e, is the formula of a linear regression, and e is the error of the model. In order to minimize the “e,” one must control for as many outside factors that may impact the dependent variable as possible. In climate science, efforts to control for exogenous factors is completely absent. In fact, by choosing the highly flawed and “adjusted” ground measurements they are effectively maximizing the impact of exogenous factors on their data set and minimizing the usefullness of their preferred data set to identify and isolate the impact of CO2 on atmospheric temperatures.

In climate science, the main model being promoted is Temperature is a…