ISyE 6644 | Fall 2020 | Test #2b Solutions
(Revised 11/6/20)
This test is 120 minutes. There are 38 questions, each worth 2.5 points, and a \free"
39th question, worth 5 points (total = 100).
In additon, later on, we
...
ISyE 6644 | Fall 2020 | Test #2b Solutions
(Revised 11/6/20)
This test is 120 minutes. There are 38 questions, each worth 2.5 points, and a \free"
39th question, worth 5 points (total = 100).
In additon, later on, we will add 4 points to everyone’s score (up to a max of 100).
But in exchange, you will not be allowed to whine about (and we will not consider) any
grade scoring issues unless they involve more than 4 points.
Let’s get some additional awyer stuff out of the way. . .
You’re allowed the following items:
• Pencil / pen and scratch paper.
• A reasonable calculator.
• Two cheat sheets (4 sides total).
• Normal, t, and χ2 tables. (I will supply these.)
But note that
• You are not allowed to use Arena, even though I’m asking questions about it.
• This test requires some sort of proctor.
• If you encounter a ProctorTrack issue, contact us immediately (but don’t get an
ulcer over it).
Good luck! I want you to make this test sorry that it ever tried to mess around with you!!!
1. Suppose X and Y are continuous random variables with joint p.d.f. f(x; y) =
cxy2; 0 ≤ x ≤ 2; 0 ≤ y ≤ 1, for some appropriate constant c. Find E[2X − 1].
(a) 1/6
(b) 5/3
(c) 5/2
(d) 11/32
(e) 12
Solution: First, we need to find c, so we set:
1 = Z0 1 Z0 2 f(x; y) dx dy
= Z0 1 Z0 2 cxy2 dx dy
=
2c
3
:
Therefore, c = 3 2. Next, we find the marginal p.d.f. fX(x):
fX(x) = Z0 1 3 2xy2 dy
= x=2; 0 ≤ x ≤ 2:
Finally, we compute E[X]:
E[X] = Z0 2 xfX(x) dx
= 4=3:
Thus, E[2X − 1] = 2E[X] − 1 = 5=3. Thus, the answer is (b). 2
2. Suppose X and Y are discrete random variables with the following joint p.m.f.
f(x; y) X = 2 X = 3 Pr(Y = y)
Y = 0 0.2 0.5 0.7
Y = 1 0.0 0.3 0.3
Pr(X = x) 0.2 0.8 1.0
Find Var(X + 2Y ).
(a) 0.16
(b) 0.21
(c) 0.49
(d) 1.243
(e) 3.14
Solution: We can compute the following quantities of interest:
E[X] = X
x
xfX(x) = 2:8
E[X2] = X
x
x2fX(x) = 8
Var(X) = E[X2] − (E[X])2 = 0:16
E[Y ] = X
y
yfY (y) = 0:3
E[Y 2] = X
y
y2fY (y) = 0:3
Var(Y ) = E[X2] − (E[X])2 = 0:21
E[XY ] = X
x
Xy
xyfX;Y (x; y) = 0:9
Cov(X; Y ) = E[XY ] − E[X]E[Y ] = 0:06
Therefore,
Var(X + 2Y ) = Var(X) + 4Var(Y ) + 4Cov(X; Y ) = 1:24:
Thus, the answer is (d). 2
3. If X and Y are independent Exp(λ = 1) random variables, find Cov(−3X; 4Y − 2).
(a) −3
(b) −2
(c) 0
(d) 0.5
(e) 1
Solution: By independence, Cov(−3X; 4Y − 2) = −12Cov(X; Y ) = 0, i.e., choice
(c)
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