A prediction interval is a range of values that is likely to contain the value of a new observation based on a statistical model, providing an estimate of uncertainty around the predicted outcome. This concept plays a crucial role in assessing how well a model can predict future data points and considers both the variability of the response variable and the uncertainty associated with estimating the parameters of the model.
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