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Material Type: Assignment; Class: Probability with Engrg Applic; Subject: Electrical and Computer Engr; University: University of Illinois - Urbana-Champaign; Term: Fall 2006;
Typology: Assignments
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University of Illinois Fall 2006
P [{Y = k} ∩ {W = l}|{X = k + l}] = P [{Y = k}|{X = k + l}] =
k + l k
pk(1 − p)l.
(b) Y and W are not conditionally independent given the event {X = n}. In fact, they are very much dependent since their sum is n.
(c) P [{Y = k} ∩ {W = l}] =
n=
P [{Y = k} ∩ {W = l}|{X = n}]P {X = n}
k + l k
pk(1 − p)l^ exp(−λ)
λk+l (k + l)!
= exp(−λp)
(λp)k k!
· exp(−λ(1 − p))
(λ(1 − p))l l! = P {Y = k} · P {W = l}. (d) Yes, Y and W are unconditionally independent, even though they are conditionally very much dependent. This particular result (called Poisson splitting) has many applications. For example, suppose that packets arriving at a server are placed into one of two queues with probabilities p and (1 − p) respectively. If the number of packets arriving per unit time is modeled as a Poisson random variable with parameter λ, then the numbers of packets in the queues can be modeled as independent Poisson random variables with parameters λp and λ(1 − p). Conversely, if the numbers of packets arriving per unit time on different ports are modeled as independent Poisson random variables with parameters λi, then the total number of packets is a Poisson random variable with parameter
λi.
0 u < 0 , u^2 , 0 ≤ u < 1 , 1 , u ≥ 1.
is a valid CDF. P {|X | > 0. 5 } = P {X > 0. 5 } = 1 − F (0.5) = 34.
(b) F (u) =
0 u < 1 , 2 u − u^2 , 1 ≤ u ≤ 2 , 1 , u > 2.
is not a valid CDF since F (1) = 1 > F (2) = 0.
(c) F (u) =
2 exp(2u)^ u^ ≤^0 , 1 − 14 exp(− 3 u), u > 0 , is^ not^ a valid CDF since it is not right-continuous at 0.
(d) F (u) =
2 exp(2u)^ u <^0 , 1 − 14 exp(− 3 u), u ≥ 0 , is a valid CDF. P {|X | > 0. 5 } = 1 − P {|X | ≤ 0. 5 } = 1 − (F (0.5) − F (− 0 .5)) = 12 exp(−1) − 14 exp(− 1 .5).
8 , and^ P^ {X^ >^2 | X^ >^0 }^ =^
(b) E[X ] is the area between the CDF and the line at height 1 as shown in the figure below. Elementary geometry gives E[X ] =^1 2
University Problem Set #8: Solutions ECE 313 of Illinois Page 1 of 2 Spring 2003
1. (a) F (^) X (1) = 1, F (^) X (3/2) = 3/4. Thus, F (^) X (u) is not a nondecreasing function and thus cannot be a valid CDF. (b) Yes. F (^) X (u) is a valid CDF, and is continuous except at u = 0. P{| X | > 0.5} = 1 -–P{| X | ≤ 0.5} = 1 – (F (^) X (0.5) – F (^) X (–0.5–)) = 1 – (F (^) X (0.5) – F (^) X (–0.5)) = 1 -–(1 – (1/4)exp(–3/2) – (1/2)exp(–1)) = (1/4)exp(–3/2) + (1/2) exp(–1). (c) F (^) X (u) is not right continuous at u = 0 and thus cannot be a valid CDF.
2.(a) P(works for exactly 2 hours) = P{ X = 2} = F (^) X (2+) – F (^) X (2–^ ) = 1/4. (b) P(works for more than 2 hours) = P{ X > 2} = 1 – F (^) X (2+) = 1/4. (c) P(works for less than 2 hours) = P{ X < 2} = F (^) X (2–^ ) = 1/2. (d) P(works for exactly 3 hours) = P{ X = 3} = F (^) X (3+) – F (^) X (3–^ ) = 0. (e) P(works for more than 1/2 but less than 3 hours) = P{1/2 < X < 3} = F (^) X (3–^ ) – F (^) X ((1/2)+) = 7/8 – 3/16 = 11/16. (f) P(works for more than 2 hours given that the student works at all) = P{ X > 2| X > 0}
= P({ X^ > 2}P{ X ∩> 0}{ X^ > 0})= P{P{ XX^ > 2}> 0} =
(g) The CDF is as shown, and as discussed in class, E[ X ] = shaded area between CDF and the line at height 1. By elementary geometry, the shaded area is 1×(7/8 + 6/8)/2 + 1/2 + (1/2)×(2)×(1/4) = 22/16 = 1.375 hours. Noncredit Exercise: How does this compare with the number reported by Eta Kappa Nu in their survey?
0
∞
0
1
1
2
2
3 P{ X >u}du + … But, X takes on only integer values.
Thus, for any given nonnegative integer k, it must be that for all u ∈ [k,k+1), P{ X > u} = P{ X > k}.
0
P {X > u} du =
k=
∫ (^) k+
k
P {X > u} du.
But, for each u ∈ [k, k + 1), P {X > u} has the same value P {X > k}. The k-th integral thus has a constant integrand P {X > k} and therefore evaluates to P {X > k}. Furthermore, if i = k+1, then P {X > k} = P {X ≥ k + 1} = P {X ≥ i}. Hence E[X ] =
k=0 P^ {X > k}^ =^
i=1 P^ {X^ ≥^ i}. (b) For k = 0, 1 , 2 ,.. ., P {X > k} = qk^ where q = 1 − p. Therefore,
k=
P {X > k} =
k=
qk^ = 1 1 − q
p
(c)
k=
k · P {X > k} =
k=
k
l=k+
pX (l). Now, for any given l, the term pX (l) will appear only in
the sums for k = 0, 1 ,... , l − 1. Hence, (using LOTUS backwards!) we can write the sum as ∑^ ∞
k=
k · P {X > k} =
l=
pX (l)
∑^ l−^1
k=
k =
l=
pX (l) ·
l(l − 1) 2
20
u^2
du =
u
∞
20
(b) FX (u 0 ) =
∫ (^) u 0
−∞
fX (u) du =
∫ (^) u 0
10
u^2
du =
u
u 0
10
u 0
. Note that FX (20) = 12 ; it should be!
(c) P {X > 15 } = 1 − FX (15) =
. Assuming that the device failures are independent, the probability that at least 3 of the 6 last for 15 hours (i.e., at most 3 fail) is a binomial probability:
P {at least 3 of 6 devices work for 15 hours} = P {at most 3 failures} =
i=
i
)i ( 2 3
) 6 −i .