Since X1,X2,X3 are uniform random variables on the interval (0, 1), their probability distribution functions are,
f(X1)=f(X2)=f(X3)=1, 0<Xi<1, i=1,2,3
0, elsewhere
E(X1)=∫01X1dx1=2X12∣01=21
E(X12)=∫01X12dx1=3X13∣01=31
Var(X1)=E(X12)−(E(X1))2=31−(21)2=121
Since X2 and X3 have the same probability distribution function as X1, they both will have the same variance as X1, that is,
Var(X1)=Var(X2)=Var(X3)=121 and
Cov(Xi,Xj)=241 for i=1,2,3, j=1,2,3, i=j
Now,
Var(2X1+X2−X3)=E[(2X1+X2−X3)−(2μ1+μ2−μ3)]2 , from definition
=E[2(X1−μ1)+(X2+μ2)−(X3−μ3)]2
=4Var(X1)+Var(X2)+Var(X3)+4Cov(X1,X2)−4Cov(X1,X3)−2Cov(X2,X3)
=4(121)+121+121+4(241)−4(241)−2(241)=126−242=125
Therefore, the variance of 2X1 + X2 − X3 is 125.
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