Advanced High-School Mathematics

(Tina Meador) #1

SECTION 6.3 Parameters and Statistics 371


Next, continuing to assume that X anY are independent random
variables, we proceed to computeE(X+Y). We have


E(X+Y) =

∫∞
−∞x(fX∗fY)(x)dx
=

∫∞
−∞x

∫∞
−∞fX(t)fY(x−t)dtdx
=

∫∞
−∞fX(t)

∫∞
−∞xfY(x−t)dtdx
=

∫∞
−∞fX(t)

∫∞
−∞(t+x)fY(x)dxdt
=

∫∞
−∞fX(t)(t+E(Y))dt
= E(X) +E(Y).

Exercises



  1. Compute the mean and the variance of the random variablerand.
    (Recall thatrandhas density function


f(x) =





1 if 0≤x≤ 1 ,
0 otherwise.)


  1. Compute the mean and the variance of the random variable



rand.
(Recall that


randhas density function

f(x) =





2 x if 0≤x≤ 1 ,
0 otherwise.)


  1. Compute the mean and the variance of the random variablerand^2.
    (See Exercise 7 on page 356.)

  2. Compute the mean and the variance of the random variable having
    density function given in Exercise 6 on page 355.

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