Let X be a random variable that takes on values between 0 and c. That is, p { 0 ≤ X ≤ c } = 1 .Show that var ( X ) ≤ c 2 4 Hint: One approach is to first argue that E [ X 2 ] ≤ c E [ X ] and then use this inequality to show that var ( X ) ≤ c 2 [ a ( 1 − a ) ] where a = E [ X ] c
Let X be a random variable that takes on values between 0 and c. That is, p { 0 ≤ X ≤ c } = 1 .Show that var ( X ) ≤ c 2 4 Hint: One approach is to first argue that E [ X 2 ] ≤ c E [ X ] and then use this inequality to show that var ( X ) ≤ c 2 [ a ( 1 − a ) ] where a = E [ X ] c
Let X be a random variable that takes on values between 0 and c. That is,
p
{
0
≤
X
≤
c
}
=
1
.Show that
var
(
X
)
≤
c
2
4
Hint: One approach is to first argue that
E
[
X
2
]
≤
c
E
[
X
]
and then use this inequality to show that
var
(
X
)
≤
c
2
[
a
(
1
−
a
)
]
where
a
=
E
[
X
]
c
Exercise 1
Mateo is the star player of a certain soccer team and is getting ready for a very important match after
spending several months recovering from an injury. If the player is injured again during this match, the
probability that his team wins is 0.32. If Mateo is not injured, the probability that his team loses is 0.18. In
addition, according to the team doctor, the probability that the player gets injured during the match is 0.15.
a. Draw a probability tree that properly represents the situation described above. Clearly label the
probabilities on each branch of the tree.
b. What is the probability that Mateo's team wins the match?
c. If Mateo's team loses the match, what is the probability that Mateo was injured?
d. Consider the event "Mateo is injured" and the event "Mateo's team wins the match." Are these events
independent? Clearly justify your answer.
A company devoted to the production and distribution of craft beer has decided to run a
quality-control check on a batch of 330 mL Porter beer bottles. A random sample of the
contents of 52 bottles was taken; the volume (in millilitres, mL) was measured and is shown
below:
Dato
Volumen
(ml)
Volumen
Volumen
Volumen
Dato
Dato
Dato
(ml)
(ml)
(ml)
333
14
326
27
330
40
329
2
328
15
331
28
329
41
327
3
335
16
331
29
329
42
323
4
330
17
333
30
332
43
330
5
331
18
332
31
334
44
332
6
326
19
327
32
336
45
333
7
330
20
330
33
328
46
328
8
329
21
328
34
326
47
329
9
332
22
325
35
330
48
327
10
334
23
330
36
332
49
331
11
333
24
334
37
333
50
333
12
336
25
332
38
331
51
328
13
327
26
325
39
334
52
336
Exercise 4
A company that manufactures engine parts has developed a new type of piston made from aluminium-
silicon alloys and other materials. The firm wishes to examine the mechanical properties of these pistons.
Specifically, it is interested in evaluating the yield strength of a piston while it is subjected to a constant
temperature of 250 °C. Here, the yield strength is the maximum stress, measured in megapascals (MPa), that
the piston can withstand before it deforms permanently.
From the first production batches, 15 pistons were randomly selected. Each was tested to determine its yield
strength (in MPa), giving the following results:
83.2, 90.1, 86.7, 102.4, 95.9, 91.3, 88.1, 84.6, 93.2, 92.6, 100.4, 86.5, 89.2, 96.8, 91.7.
Assuming that the yield strength of this type of piston follows a Normal distribution, construct a 96 %
confidence interval for the variance, σ², of the pistons' yield strength.
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