Question: How big is the probability density that a least squares model with true parameters would give experimental results implying a different set of parameters ?

How big is the probability density that a least squares model with true parameters would give experimental results implying a different set of parameters ? Show that it depends only on the distance between the vectors |y() y()| in the space of predictions

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