Squaring and Cancelling Out Errors and How are Tornadoes Forecasted?

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The mathematical advantages of squaring errors are evident from their use while analyzing the overall performance of linear regression (Daryal & Kumar, 2012). This allows us to partition the variation in a particular dataset into the variation that is explained by randomness and the variation that is explained by the model. It should be noticed that errors are the deviations of the mean, so squaring errors will help eliminate the negative signs of deviations. At the same time, we have to remember that canceling errors is not effective because this will mean that the error term is zero. Plus, it will look like the significance of having the error term (which consists of the effects of different factors rather than the main of the model) is lost or is not taken care of.
It is too difficult to forecast tornadoes, which is because they do not last for long and are quite complex. Scientists do not have an idea of how torna...