Prediction & Interval Estimation

Build regression interval skills for calibration, production and service forecasting. Prerequisites: simple linear regression, residual variance and t inference. Distinguish estimation of a conditional mean from prediction of one reading or a future average; compute widths, investigate design effects and assess extrapolation, dependence and coverage. Original questions progress from interpretation to uncertainty decomposition, with worked calculations and explanations of every alternative.

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