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SOLVED: Consider a weighted multiple linear regression model with n observations and p predictors, Y = Xβ e, where Y = (Y1, ..., Yn) is the n×1 vector of responses; X is the n×(p 1) matrix of predictors, including a column of 1's for the intercept; and e = (e1, ..., en) is the n×1 vector of statistical errors. Here ei's are independent normal random variables with mean 0 and variance σ^2/wi. The values of wi: i = 1, ..., n are known. Let ˆY = (ˆY1, ..., ˆYn)^T denote the fitted values
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