Probability & Random Variables Exam I for Electronic Engineering Students, Kyung Hee Unive, Exams of Probability and Stochastic Processes

An exam for the probability and random variables course in the department of electronic engineering at kyung hee university, held in fall 2017. The exam covers chapters 1-3 and includes five problems. Students are required to find probabilities, conditional probabilities, and expected values for various random variables. The document also includes instructions for calculating the probability mass function (pmf) and cumulative distribution function (cdf).

Typology: Exams

2017/2018

Uploaded on 09/14/2018

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Kyung Hee University
Department of Electronic Engineering
Probability and Random Variables
Fall 2017: Exam I
Hyundong Shin
October 12, 2017
16:30 17:50 (80 minutes)
Chapters 1–3 (120 points): Show all relevant work.
Problem 1 (50 points)
Suppose that binary symbols are transmitted over the channel XYas shown in the following
figure where each transmission is statistically independent.
Note that P[X= 0] = P[X= 1] = 1/2and each label on the arrow denotes the conditional
probability. For example,
=P[Y= 1|X= 0] = P[Y= 0|X= 1] .
Use (x, y)to denote
(X=x, Y =y).
(a) (10 points) Find the sample space S.
(b) (10 points) Find the probability of erasure P[Y=E]and the probability of error P[X6=Y, Y 6=E].
(c) (10 points) Find P[X= 1|Y= 0].
(d) (10 points) Transmit 100 bits over the channel. Find the probability of 10 errors and 5 erasures
in this 100 independent trials.
(e) (10 points) Let Zbe the number of transmitted bits until the first successful reception comes
up. Find the probability mass function (PMF) PZ(z)of Z.
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Kyung Hee University Department of Electronic Engineering

Probability and Random Variables

Fall 2017: Exam I

Hyundong Shin October 12, 2017 16:30 – 17:50 (80 minutes)

Chapters 1–3 (120 points): Show all relevant work.

Problem 1 (50 points)

Suppose that binary symbols are transmitted over the channel X → Y as shown in the following figure where each transmission is statistically independent.

Note that P [X = 0] = P [X = 1] = 1/ 2 and each label on the arrow denotes the conditional probability. For example,

 = P [Y = 1|X = 0] = P [Y = 0|X = 1].

Use (x, y) to denote (X = x, Y = y).

(a) (10 points) Find the sample space S. (b) (10 points) Find the probability of erasure P [Y = E] and the probability of error P [X 6 = Y, Y 6 = E]. (c) (10 points) Find P [X = 1|Y = 0]. (d) (10 points) Transmit 100 bits over the channel. Find the probability of 10 errors and 5 erasures in this 100 independent trials. (e) (10 points) Let Z be the number of transmitted bits until the first successful reception comes up. Find the probability mass function (PMF) PZ (z) of Z.

Problem 2 (40 points)

The random variable X has the PMF

PX (x) =

c/x, x = 2, 4 , 8 0 , otherwise. (a) (10 points) Find the constant c. (b) (10 points) Find and carefully draw the cumulative distribution function (CDF) FX (x) of X. (c) (10 points) Find P [1 ≤ X ≤ 5]. (d) (10 points) Find E

[

X^2

]

and Var

[

X^2

]

Problem 3 (30 points)

The number of emails receiving in any time interval is a Poisson random variable. Let X be the number of received emails in one hour such that the probability of receiving at least one email, i.e., P [X ≥ 1] is equal to 1 − e−μ.

(a) (10 points) Find the PMF PX (x) of X. (b) (10 points) Find E [3X + 1] and Var [3X + 1]. (c) (10 points) Find the probability of no email in one day.