Let W be a gamma random variable with parameters ( t , β ) and suppose that conditional on W = ω , X 1 , X 2 , ... X n are independent exponential random variables with rate ω . Show that the conditional distribution of W given that X 1 = x 1 , X 2 = x 2 , ... , X n = x n is gamma with parameters ( t + n , β + ∑ i = 1 n x i ) .
Let W be a gamma random variable with parameters ( t , β ) and suppose that conditional on W = ω , X 1 , X 2 , ... X n are independent exponential random variables with rate ω . Show that the conditional distribution of W given that X 1 = x 1 , X 2 = x 2 , ... , X n = x n is gamma with parameters ( t + n , β + ∑ i = 1 n x i ) .
Let W be a gamma random variable with parameters
(
t
,
β
)
and suppose that conditional on
W
=
ω
,
X
1
,
X
2
,
...
X
n
are independent exponential random variables with rate
ω
. Show that the conditional distribution of W given that
X
1
=
x
1
,
X
2
=
x
2
,
...
,
X
n
=
x
n
is gamma with parameters
(
t
+
n
,
β
+
∑
i
=
1
n
x
i
)
.
Q prove or disprove: If Ely/x) = x = c(dipy
=BCCo
(BVC)
ECxly)=y, and E(X2), Ely)
In a small office, there are m = 5 typists who need to use a single typewriter to complete their reports. Assume the time
each typist takes to prepare a report follows an exponential distribution with an average of 20 minutes per preparation
(A = 3 reports/hour), and the service time for the typewriter to type out a report also follows an exponential distribution,
averaging 30 minutes to complete a report (μ 2 reports/hour). Given that the number of typists is finite and all typists
=
share one typewriter, they will form a waiting queue.
(1). Describe this queuing system and explain how it fits the characteristics of the M/M/1/∞0/m model.
(2). Calculate the probability that any typist is using the typewriter at steady-state.
(3). Calculate the average number of typists waiting in the queue at steady-state.
(4). Considering the need to reduce waiting time, if an additional typewriter is introduced (turning into a two-server
system, or M/M/2/∞0/m model), analyze the expected impact,…
Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, probability and related others by exploring similar questions and additional content below.
Continuous Probability Distributions - Basic Introduction; Author: The Organic Chemistry Tutor;https://www.youtube.com/watch?v=QxqxdQ_g2uw;License: Standard YouTube License, CC-BY
Probability Density Function (p.d.f.) Finding k (Part 1) | ExamSolutions; Author: ExamSolutions;https://www.youtube.com/watch?v=RsuS2ehsTDM;License: Standard YouTube License, CC-BY
Find the value of k so that the Function is a Probability Density Function; Author: The Math Sorcerer;https://www.youtube.com/watch?v=QqoCZWrVnbA;License: Standard Youtube License