University of California Davis Random Variable Worksheet

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University of California Davis

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EE 503 : Homework 3 Due : 09/23/2021, Thursday before class. 1. An urn contains n + m balls, of which n are red and m are black. They are drawn from the urn one at a time, without replacement. Let X be the number of red balls removed before the first black ball is chosen. We are interested in determining E[X]. To obtain this quantity, number the red balls from 1 to n. Now define the random variables Xi , i = 1, · · · n, by   1, if red ball i is taken before any black ball is chosen Xi =  0, otherwise a) Express X in terms of the Xi . b) Find E[X]. 2. Let X be a uniformly distributed random variable in the interval [−π, π]. What is the cdf of Y = tan X? 3. If X ∼ N (µ, σ), what is the pdf of Y = (X − µ)2 /σ 2 ? 4. A Cauchy random variable X has the following pdf fX (x) = π(x2 α , −∞ < x < ∞, α > 0 + α2 ) a) Find E[X] and E[X 2 ]? b) Suppose a random variable X had a characteristic function φ(ω) = e−|ω| , what is its mean and variance? 5. Three types of customers arrive at a service station. The times required to service type 1 and type 2 customers are exponential random variables with respective means 1 and 10 seconds. Type 3 customers require a constant service time of 2 seconds. Suppose that the proportion of type 1, 2 and 3 customers is 1/2, 1/8 and 3/8, respectively. Find the probability that an arbitrary customer requires more than 15 seconds of service time. 6. The average score in the final exam of a course is 65 and the standard deviation is 10. a) Give an upper bound on the probability of a student scoring more than 95? b) Suppose the scores follow a normal distribution. Compute the probability of a student scoring more than 95 and compare it to the bound obtained in a). 7. The number X of electrons counted by a receiver in an optical communication system is a Poisson random variable with rate λ1 when a signal is present and with rate λ0 < λ1 when a signal is absent. Suppose that a signal is present with probability p. a) Find P [signal present|X = k] and P [signal absent|X = k]. b) The receiver uses the following decision rule: If P [signal present|X = k] > P [signal absent|X = k], decide signal present; otherwise decide signal absent Show that this decision rule leads to the following threshold rule: If X > T , decide signal present; otherwise, decide signal absent. c) What is the probability of error for the above decision rule? 8. Exponential Random Variable: a) Generate instances of exponential random distribution from a uniform distributed random variable, random.uniform(0,1). b) Use the built-in function random.exponential() to generate the same number of instances. c) Compare the histograms of a and b. 2
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EE 503: Homework 3
Due: 09/23/2021
Student’s name:
Instructor:

1

1) An urn contains n + m balls, of which n are red and m are black. They are
withdrawn from the urn, one at a time and without replacement. Let X is the
number

of

red

balls

removed

before

the

first

black

is

chosen.

We

are

interested in determining E[X]. To obtain this quantity, number the red balls
from 1 to n. Now define the random variables Xi, i=1,...,n, by

1,
Xi = 
0,

if red ball i is taken before any black ball is chosen
Otherwise

a) Express X in terms of Xi.

ANS:
The random variable X represents the number of red balls removed before the first black ball is chosen.
Thus, X can be represented in terms of Xi, as follows:
X = ∑𝑛𝑖=𝑖 𝑋𝑖
= X1 + X2 + …+ Xn

b) Find E[X].

ANS:
If 1 red ball is chosen before black ball then,
𝑛 𝑛
X1 = ( )(𝑚+𝑛)
1
If 2 red ball is chosen before black ball then,
𝑛 𝑛
𝑛 − 1 𝑛−1
X2 = ( )(𝑚+𝑛) + (
)(𝑚+𝑛−1)
1
1
If n red ball is chosen before black ball then,
𝑛 𝑛
𝑛 − 1 𝑛−1
1 −1
Xn = ( )(𝑚+𝑛) + (
)(𝑚+𝑛−1)+…+ ( )(𝑚+1)
1
1
1
𝑛

E[X]= E [∑𝑛𝑖=𝑖 𝑋𝑖 ]= E [X1 + X2 + …+ Xn] =E [X1]+ E [X2]+…+ E [Xn]= 𝑚+1

E[X]=

𝑛
𝑚+1

2

2) Let X be a uniformly distributed random variable in the interval [−π,π]. What is the cdf of Y
=tanX?
ANS:
𝑙𝑒𝑡 𝑥 ~𝑣(−𝜋, 𝜋)
𝑝𝑑𝑓 𝑜𝑓 𝑥;
𝑓(𝑥) =

1
, ...

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