Resolution for Assignment 5 - Engineering Probability - Fall 2002 | ENEE 324, Assignments of Probability and Statistics

Material Type: Assignment; Professor: Olfat; Class: ENG PROBABILITY; Subject: Electrical & Computer Engineering; University: University of Maryland; Term: Fall 2002;

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Univ. Of Maryland at College Park, ECE Department
ENEE324 Fall 2002 Instructor: M. Olfat
Solution to Assignment #: 5 Posted on: 10/09/02
a)
Net reward 2
yaxbxnd
=+−
, where
x
is binomial.
[
]
(
)
(
)
(
)
(
)
(
)
222
0000
1
XXXX
xxxx
EyEaxbxndaxbxndPxaxPxbxPxndPx
====
=

=+=+=+−

∑∑∑
14243
[ ] [ ]
( )
( )
[ ]
2
2var

=+=++−
 

(
)
(
)
(
)
22 11
anpnppbnpndanpnppbnpnd
=+−+=++−
b)
x
ya
=
[ ]
( ) ( ) ( ) ( )
00
111
n
nn
nkknk
xkk
kk
nn
EyEaappappapp
kk
−−
==



====+−


 
∑∑
by Khayyam-Newton formula
a)
(
)
10
PY
<=
b)
(
)
(
)
110.25
Y
PYF==
c)
(
)
(
)
(
)
2121210.50.5
Y
PYPYF>===−=
d)
(
)
(
)
(
)
(
)
212111110.250.75
Y
PYPYPYF=<===−=
e)
(
)
(
)
(
)
1100.2500.25
YY
PYFF==−=−=
f)
(
)
(
)
(
)
33210.50.5
YY
PYFF==−=−=
g)
( )
0.25 1
0.25 2
0.5 3
0 otherwise
Y
y
y
Py y
=
=
==
Problem 2
: [YAT]2.4.1
Problem 1
: [
GAR
]
3.75
pf3
pf4
pf5

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Download Resolution for Assignment 5 - Engineering Probability - Fall 2002 | ENEE 324 and more Assignments Probability and Statistics in PDF only on Docsity!

Univ. Of Maryland at College Park, ECE Department

ENEE324 Fall 2002 Instructor : M. Olfat

Solution to Assignment #: 5 Posted on: 10/09/

a)

Net reward

2

y = ax + bxnd , where x is binomial.

[ ] ( )

( ) ( ) ( ) ( )

2 2 2

0 0 0 0

1

X X X X

x x x x

E y E ax bx nd ax bx nd P x a x P x b xP x nd P x

= = = =

=

∑ ∑ ∑ ∑

[ ] ( [ ]) ( ) [ ]

2

2

aE x bE x nd a E x var x bE x nd

( ) ( )

( )

2 2

= a n p + np 1 − p + bnpnd = anp np + 1 − p + bnpnd

b)

x

y = a

[ ] ( ) ( ) ( ) ( )

0 0

n

n n

n k k n k

x k k

k k

n n

E y E a a p p ap p ap p

k k

− −

= =

∑ ∑

by Khayyam-Newton formula

a) ( )

P Y < 1 = 0

b) ( ) ( )

Y

P Y ≤ = F =

c) ( ) ( ) ( )

Y

P Y > = − P Y ≤ = − F = − =

d) ( ) ( ) ( ) ( )

Y

P Y ≥ = − P Y < = − P Y ≤ = − F = − =

e) ( ) ( ) ( )

Y Y

P Y = = F − F = − =

f) ( ) ( ) ( )

Y Y

P Y = = F − F = − =

g) ( )

0 otherwise

Y

y

y

P y

y

Problem 2: [YAT]2.4.

Problem 1: [GAR]3.

[ ] ( )

0

x

k

E x kP k

=

. Instead of k we can write

1

k

l

k

=

[ ] ( ) ( )

0 1 0 1

k k

X X

k l k l

E x P k P k

∞ ∞

= = = =

∑ ∑ ∑∑

We can change the order of sums:

[ ] ( )

0 1

k

X

k l

E x P k

= =

∑∑

k = 0

k = 1

k = 2

k = 3

k = 4

( )

0 terms 0

X

P

1 terms ( 1 ) X

P

2 terms ( 2 )

X

P

3 terms ( 3 ) X

P

4 terms ( 4 ) X

P

So: [ ] ( ) ( ) ( ) ( )

0 1 0 1 0 0

k

X X X

k l l k l l

E x P k P k P x l P x l

∞ ∞ ∞ ∞ ∞

= = = = + =

∑∑ ∑ ∑ ∑ ∑

a)

( ) ( )

2

U Y

y u y

P u P y

=

but in problem 2.4.1 : { }

y ∈1,2,

So

2

u = y has only one solution y = u

Problem 3: [YAT]2.5.

Problem 4: [YAT]2.6.

[ ]

( ) ( ) ( )

3 3 3 3 3 3 3

2 3

X X

x S x S

x x

E x x

∈ ∈

∑ ∑

b)

( ) ( )

( )

2 2

: , 0 X X

Z X X

x z x S x x S x z

P z P x P x

= ∈ ∈ − =

∑ ∑

( ) ( )

( ) ( ) ( )

( )

( ) ( ) ( )

( )

( ) ( ) ( )

( )

( )

2

2

2

2

2

2

0 otherwise 9 3 3

Z X

Z X X

Z

Z X X

Z X X

P P

z

P P P

z

P z

P P P

z

P P P

c)

( ) ( [ ]) [ ]

2 1 2 9 1 8 81 1 16 81 98

Var 1 4 9 7

x E x E x E z

= − = = × + × + × = + + = = =

d)

( ) [ ] ( )

( ) ( )

4

2

2

Var

X X X

X X

x S x S x S

x

x x E x P x x P x

∈ ∈ ∈

∑ ∑ ∑

( ) ( ) ( )

4 4 4

4 4 4

e)

( )

4

2 2

X X

X

x S x S

x

E x x P x

∈ ∈

∑ ∑

( ) ( [ ])

2

2 2

Var x E x E x 7 0 7

Take x as the number of girls among natural children. Then it has a binomial distribution with

parameters 5 and

( )

5 5

0 otherwise

x x

X

x

P x x x

Problem 7:

If y is the number of girls among all children, then y = x + 2.

So:

( ) ( )

{ }

( )

2

Y X X

x x y

P y P x P y

  • =

Note that the equation y = x + 2 has only one solution x = y − 2 and so we don’t need ∑

Also 0 ≤ y − 2 ≤ 5 ⇒ 2 ≤ y ≤ 7. So:

( )

5

0 otherwise

Y

y

P y y