Regressing with zero covariance

Random variables XX and YY satisfy E[X]=6E[X] = 6, V[X]=2V[X] = 2, E[Y]=8E[Y] = 8, V[Y]=10V[Y] = 10, and Cov⁡(X,Y)=0\operatorname{Cov}(X, Y) = 0. You fit a simple linear regression predicting YY from XX, obtaining Y^=aX+b\hat Y = aX + b. What is a+ba + b?

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  1. Slope a=Cov⁡(X,Y)/V[X]a=\operatorname{Cov}(X,Y)/V[X]. What is it when Cov⁡=0\operatorname{Cov}=0?
  2. a=0a=0, and b=E[Y]−a E[X]=8b=E[Y]-a\,E[X]=8, so a+b=8a+b=8.

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