# Question

Use Theorem 4.14 on page 135 and its corollary to show that if X11, X12, . . . , X1n1 , X21, X22, . . . , X2n2 are independent random variables, with the first n1 constituting a random sample from an infinite population with the mean µ1 and the variance σ21 and the other n2 constituting a random sample from an infinite population with the mean µ2 and the variance σ22 , then

(a) E(1 – 2) = µ1 – µ2;

(b) var(1 – 2) = σ21/n1 + σ22/n2 .

Theorem 4.14

If X1, X2, . . . , Xn are random variables and

Where a1, a2, . . . , an are constants, then

And

Where the double summation extends over all values of i and j, from 1 to n, for which i < j.

(a) E(1 – 2) = µ1 – µ2;

(b) var(1 – 2) = σ21/n1 + σ22/n2 .

Theorem 4.14

If X1, X2, . . . , Xn are random variables and

Where a1, a2, . . . , an are constants, then

And

Where the double summation extends over all values of i and j, from 1 to n, for which i < j.

## Answer to relevant Questions

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