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A series of statistical problems related to various distributions, such as gamma, normal, uniform, exponential, beta, and gamma distributions. It covers topics such as moment generating functions, means, medians, and expected monetary values. The problems require the use of statistical formulas and properties to find solutions.
Typology: Exams
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1
0
1 1
0
1 /
y
-
3
4 1 / 4
0
4
0
3
y dy y m m
m m
th
k
1
0
1
0
1
k k k
0 ( ). 6065
30
1 ( 15 )
1 / 2
15
/ 30
15
/ 30
P Y e dy e e
y y
Derive the moment generating function for the exponential distribution with mean .
0 1
0
0
/
0
exp 1
exp
e e t t
y t
t
M t e e dy y t dy
ty y
A computer program generates pseudo-random numbers from a Uniform(0,1)
distribution. If it is working properly, what is the probability it will return 4 consecutive
numbers greater than 0.75?
(.25)
4 =.
The amount of impurity in batches of a chemical follow a Beta distribution with =1, and
=2.
Give the density function, as well as the mean amount of impurity.
f(y) = 2(1-y) 0≤ y ≤ 1
E(Y) = 1/(1+2) = 1/
If the amount of impurity exceeds 0.7, the batch cannot be sold. What proportion
of batches can be sold?
2 ( 1 ) 2 1. 4 0. 49 0. 91
0
2
0
ydy y y
Lifetimes of electrical components follow a Gamma distribution with =3, and =
Give the density function(be very specific to any numbers), as well as the mean
and standard deviation of the lifetimes.
f(y) = (1/432)y
2 e
-y/ y>
E(Y) = 18
Y = (3(6)
2 ) = 10.
The monetary value to the firm of a component with a lifetime of Y is V = 3Y
2
Y – 1. Give the expected monetary value of a component.
E(Y
2 ) = 108+(18)
2 = 432 E(V) = 3(432) + 18 -1 = 1313