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Recall that
Var[aX + bY] = a ² Var[X] + 2ab Cov[X, Y] + b ² Var[Y]
Then
Var[3X - 7Y] = 9 Var[X] - 42 Cov[X, Y] + 49 Var[Y]
Now, standard deviation = square root of variance, so
Var[3X - 7Y] = 9×6² - 42×2 + 49×8² = 3376
The general result is easy to prove: by definition,
Var[X] = E[(X - E[X])²] = E[X ²] - E[X]²
Cov[X, Y] = E[(X - E[X]) (Y - E[Y])] = E[XY] - E[X] E[Y]
Then
Var[aX + bY] = E[((aX + bY) - E[aX + bY])²]
… = E[(aX + bY)²] - E[aX + bY]²
… = E[a ² X ² + 2abXY + b ² Y ²] - (a E[X] + b E[Y])²
… = E[a ² X ² + 2abXY + b ² Y ²] - (a ² E[X]² + 2 ab E[X] E[Y] + b ² E[Y]²)
… = a ² E[X ²] + 2ab E[XY] + b ² E[Y ²] - a ² E[X]² - 2 ab E[X] E[Y] - b ² E[Y]²
… = a ² (E[X ²] - E[X]²) + 2ab (E[XY] - E[X] E[Y]) + b ² (E[Y ²] - E[Y]²)
… = a ² Var[X] + 2ab Cov[X, Y] + b ² Var[Y]