Problem Set for ECE 313: Spring 1998 - Probability Theory, Assignments of Statistics

Problem set #9 for the university of illinois ece 313 course in spring 1998. The problem set covers various topics in probability theory, including finding probability mass functions, expected values, variances, and percentages of defective items. Students are expected to solve problems related to ranking of scores, number of rounds in a game, poisson random variables, and gaussian random variables.

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University of Illinois Spring 1998
ECE313: Problem Set #9
Assigned: October 21, 1998
Due: October 28, 1998
Reading: Ross, Chapters 4 and 5
Additional problems: 4.20–4.23, 4.25, 4.27, 4.28, 4.32–4.40, 4.42, 4.43, 4.46, 4.48, 4.50, 4.51
1. Suppose that five boys and five girls are ranked according to their scores on an exam. Assume
that no two scores are alike, and that all the
10!
rankings are equally likely. Let
X
denote the
highest ranking achieved by a girl. For example, if the top-ranked person is a girl, then
X
=1
.
If the top-ranked girl is ranked second overall, then
X
=2
, and so forth.
(a) Find the probability mass function of
X
.
(b) Compute the expected value and variance of
X
.
2. A box contains 4 white balls and 4 black balls, and the following game is played. Each round of
the game consists of randomly selecting four balls from the box. If exactly two of them are white,
the game is over. Otherwise, the four balls are placed back in the box, so that it again contains 4
white balls and 4 black balls before the next round is performed. The rounds are repeated until
exactly two of the chosen balls are white.
(a) Let
X
denote the number of rounds in this game. Find the expected value and the variance
of
X
.
(b) When the game is over, we get a reward
Y
. The value of
Y
decreases exponentially with
the the number of rounds played. Specifically, if the game terminates after
n
rounds, then
Y
=1
=e
n
. Find the expected value of the reward
Y
.
3. Suppose that the continuous random variable
X
has probability density function
f
X
(
u
)
defined
as follows:
f
X
(
u
)=
c
(1
,
u
)
2
for
0
<u<
1
,and
f
X
(
u
)=0
elsewhere.
(a) Find the value of the constant
c
.
(b) Find the mean and the variance of
X
.
(c) Compute
P
(6
X
2
>
5
X
+1)
and
P
(6
X
2
>
7
X
,
2)
.
4. Let
X
denote a Poisson random variable with parameter
=0
:
5
.
(a) Compute
E
[
X
!]
.
(b) Show that
E
[
X
n
]=0
:
5
E
[(
X
+1)
n
,
1
]
.
(c) Use this result to compute
E
[
X
3
]
.
pf2

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University of Illinois Spring 1998

ECE 313: Problem Set

Assigned: October 21, 1998

Due: October 28, 1998

Reading: Ross, Chapters 4 and 5

Additional problems: 4.20–4.23, 4.25, 4.27, 4.28, 4.32–4.40, 4.42, 4.43, 4.46, 4.48, 4.50, 4.

1. Suppose that five boys and five girls are ranked according to their scores on an exam. Assume

that no two scores are alike, and that all the 10! rankings are equally likely. Let X denote the

highest ranking achieved by a girl. For example, if the top-ranked person is a girl, then X = 1.

If the top-ranked girl is ranked second overall, then X = 2 , and so forth.

( a) Find the probability mass function of X.

( b) Compute the expected value and variance of X.

2. A box contains 4 white balls and 4 black balls, and the following game is played. Each round of

the game consists of randomly selecting four balls from the box. If exactly two of them are white,

the game is over. Otherwise, the four balls are placed back in the box, so that it again contains 4

white balls and 4 black balls before the next round is performed. The rounds are repeated until

exactly two of the chosen balls are white.

( a) Let X denote the number of rounds in this game. Find the expected value and the variance

of X.

( b) When the game is over, we get a reward Y. The value of Y decreases exponentially with

the the number of rounds played. Specifically, if the game terminates after n rounds, then

Y = 1 =en^. Find the expected value of the reward Y.

3. Suppose that the continuous random variable X has probability density function fX (u) defined

as follows: fX (u) = c(1 u)^2 for 0 < u < 1 , and fX (u) = 0 elsewhere.

( a) Find the value of the constant c.

( b) Find the mean and the variance of X.

( c) Compute P (6X 2 > 5 X + 1) and P (6X 2 > 7 X 2).

4. Let X denote a Poisson random variable with parameter  = 0 : 5.

( a) Compute E [X !].

( b) Show that E [X n^ ] = 0 : 5 E [(X +1)n^1 ].

( c) Use this result to compute E [X 3 ].

5. The width of a screw produced by a steel company is a Gaussian random variable with mean

 = 0 : 9 cm and standard deviation  = 0 : 003 cm.

( a) If the width specification limits of a customer are 0 : 9  0 : 005 cm, and a screw whose width

is not within these limits is deemed defective, what percentage of the screws produced by

the company will be defective?

( b) The CEO’s goal is to make sure that, on the average, no more than 1 in 100 screws produced

are defective. What is the maximum allowable value of  that will enable the company to

achieved this goal?

( c) Assume that  = 0 : 9 cm and  = 0 : 003 cm as before, but the customer changes specifica-

tion limits to a minimum of 0.896 cm and a maximum 0.908 cm. What percentage of the

screws produced will be defective now?

6. Let X be a Gaussian random variable with mean  = 1 and variance  2 = 4.

( a) Find the mean and variance of 2 X + 5

Let (x) denote the CDF of a standard Gaussian random variable, and let Q(x) = 1 (x).

Suppose that Calculator A can evaluate only (x) and only for nonnegative values of x. On

the other hand, suppose that Calculator B can evaluate only Q(x), again only for x  0. Both

calculators can perform standard functions, like addition and multiplication. For each of the

probabilities in parts ( b ) through ( e ), write down two alternative expressions: one for evaluation

using Calculator A, and the other for evaluation using Calculator B.

( b) P (X < 0)

( c) P ( 10 < X < 5)

( d) P (jX j  5)

( e) P (X 2 3 X + 2 < 0)