R: Current Knowledge on Modeling
Statistics exist to help make sense of a data set. However, statistics should only be used if you pick a model that makes the same assumptions as your data does. For example, you should only take the least squares and make a linear fit if the data is reasonably linear. This is true for any other type of fit as well such as quadratic or exponential. If you don’t look at your data beforehand and take the linear fit of widely dispersed data, you will produce an output that makes no sense. I found Gigerenzer’s Mindless Statistics to be very interesting in this topic. He stated that the founders of statistics had strict debates about statistics, and had conflicting ideas. None of them thought that there should be one method for all hypotheses. I have been guilty of falling down the path of simply applying the “null ritual” in the past. Some questions do not require the Fisher and Neyman-Pearson hybrid. Instead, the model should be thought more cr...
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