The least squares estimate correctly weighted by !:. -1 is x = (AT!:. -1 A) -1 AT!:. -1 b. Call that x = Lb. If b contains an error vector e , then x contains the error Le. The covariance matrix of those output errors Le is their expected value (average value) P = E [(Le)(Le)T] = LE [eeT] LT = L!:.LT. Problem: Do the multiplication L!:.LT to show that P equals (AT!:.-l A)-I as predicted in equation (10).

L11 - 13 We c∞n modify our shortcut method for an indeterminate limit : ∞ x ex. Evaluatex→−∞m 2x −√ 4x − x x (formal method) = lim ▯ x→−∞ 2x...