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Page 1: More Discrete Random Variable Solved Problems

7242019 More Discrete Random Variable Solved Problems

httpslidepdfcomreaderfullmore-discrete-random-variable-solved-problems 15

325 Solved Problems

More about Discrete Random Variables

Problem 1

Let be a discrete random variable with the following PMF

Find and plot the CDF of

Solution

The CDF is defined by We have

Problem 2

Let be a discrete random variable with the following PMF

a Find b Find Var

c If find

Solutiona

b We can use Var Thus we need to find Using LOTUS we have

Thus we have

X

( 983160 ) = P

X

0 3

0 2

0 3

0 2

0

f o r 983160 = 3

f o r 983160 = 5

f o r 983160 = 8

f o r 983160 = 1 0

o t h e r w i s e

X

( 983160 ) = P ( X le 983160 ) F

X

( 983160 ) = F

X

0

( 3 ) = 0 3 P

X

( 3 ) + ( 5 ) = 0 5 P

X

P

X

( 3 ) + ( 5 ) + ( 8 ) = 0 8 P

X

P

X

P

X

1

f o r 983160 lt 3

f o r 3 le 983160 lt 5

f o r 5 le 983160 lt 8

f o r 8 le 983160 lt 1 0

f o r 983160 ge 1 0

X

( 983147 ) = P

X

0 1

0 4

0 3

0 2

0

f o r 983147 = 0

f o r 983147 = 1

f o r 983147 = 2

f o r 983147 = 3

o t h e r w i s e

E X

( X )

Y = ( X minus 2 )

2

E Y

E X

= ( ) sum

isin 983160

983147

R

X

983160

983147

P

X

983160

983147

= 0 ( 0 1 ) + 1 ( 0 4 ) + 2 ( 0 3 ) + 3 ( 0 2 )

= 1 6

( X ) = E minus ( E X = E minus ( 1 6 X

2

)

2

X

2

)

2

E X

2

E = ( 0 1 ) + ( 0 4 ) + ( 0 3 ) + ( 0 2 ) = 3 4 X

2

0

2

1

2

2

2

3

2

2

7242019 More Discrete Random Variable Solved Problems

httpslidepdfcomreaderfullmore-discrete-random-variable-solved-problems 25

c Again using LOTUS we have

Problem 3

Let be a discrete random variable with PMF

Define Find the PMF of

Solution

First note that Thus

Thus

Problem 4

Let Find

Solution

The PMF of is given by

where Thus

V a r ( X ) = ( 3 4 ) minus ( 1 6 = 0 8 4 )

2

E ( X minus 2 = ( 0 minus 2 ( 0 1 ) + ( 1 minus 2 ( 0 4 ) + ( 2 minus 2 ( 0 3 ) + ( 3 minus 2 ( 0 2 ) = 1 )

2

)

2

)

2

)

2

)

2

X

( 983147 ) = P

X

0 2

0 2

0 3

0 3

0

f o r 983147 = 0

f o r 983147 = 1

f o r 983147 = 2

f o r 983147 = 3

o t h e r w i s e

Y = X ( X minus 1 ) ( X minus 2 ) Y

= 983160 ( 983160 minus 1 ) ( 983160 minus 2 ) | 983160 isin 0 1 2 3 = 0 6 R

Y

( 0 ) P

Y

= P ( Y = 0 ) = P ( ( X = 0 ) o r ( X = 1 ) o r ( X = 2 ) )

= ( 0 ) + ( 1 ) + ( 2 ) P

X

P

X

P

X

= 0 7

( 6 ) P

Y

= P ( X = 3 ) = 0 3

( 983147 ) = P

Y

0 7

0 3

0

f o r 983147 = 0

f o r 983147 = 6

o t h e r w i s e

X sim G 983141 983151 983149 983141 983156 983154 983145 c ( 983152 ) E 983131 983133

1

2

X

X

( 983147 ) = 983163 P

X

983152 983153

983147 minus 1

0

f o r 983147 = 1 2 3

o t h e r w i s e

983153 = 1 minus 983152

E 983131 983133

1

2

X

= ( 983147 ) sum

infin

983147 = 1

1

2

983147

P

X

= 983152 sum

infin

983147 = 1

1

2

983147

983153

983147 minus 1

=

983152

2

sum

infin

983147 = 1

( 983081

983153

2

983147 minus 1

=

983152

2

1

1 minus

983153

2

=

983152

1 + 983152

7242019 More Discrete Random Variable Solved Problems

httpslidepdfcomreaderfullmore-discrete-random-variable-solved-problems 35

Problem 5

If find

Solution

The PMF of is given by

where

Finding directly seems to be very complicated So lets try to see if we can find an easier way to find

In particular a powerful tool that we have is linearity of expectation Can we write as the sum of

simpler random variables To do so lets remember the random experiment behind the hypergeometric

distribution You have a bag that contains blue marbles and red marbles You choose marblesat random (without replacement) and let be the number of blue marbles in your sample In particular lets

define the indicator random variables as follows

Then we can write

Thus

To find we note that for any particular all marbles are equally likely to be chosen This is

because of symmetry no marble is more likely to be chosen than the th marble as any other marblesTherefore

We conclude

Thus we have

Problem 6

In Example 314 we showed that if then We found this by writing as the sum

of random variables Now find directly using Hint Use

Solution

X sim H 983161 983152 983141 983154 983143 983141 983151 983149 983141 983156 983154 983145 c ( b 983154 983147 ) E X

X

( 983160 ) = P

X

( 983081 ( )

b

983160

983154

983147 minus

983160

( 983081

b + 983154

983147

0

f o r 983160 isin R

X

o t h e r w i s e

= m a x ( 0 983147 minus 983154 ) m a x ( 0 983147 minus 983154 ) + 1 m a x ( 0 983147 minus 983154 ) + 2 m i n ( 983147 b ) R

X

E X

E X X

X

983145

b 983154 983147 le b + 983154

X

X

983145

= 983163 X

983145

1

0

i f t h e 983145 t h c h o s e n m a r b l e i s b l u e

o t h e r w i s e

X = + + ⋯ + X

1

X

2

X

983147

E X = E + E + ⋯ + E X

1

X

2

X

983147

P ( = 1 ) X

983145

X

983145

983145

P ( = 1 ) = f o r a l l 983145 isin 1 2 ⋯ 983147 X

983145

b

b + 983154

E X

983145

= 0 sdot 983152 ( = 0 ) + 1 sdot P ( = 1 ) X

983145

X

983145

=

b

b + 983154

E X =

983147 b

b + 983154

X sim B 983145 983150 983151 983149 983145 a 983148 ( 983150 983152 ) E X = 983150 983152 X

983150 B 983141 983154 983150 983151 983157 983148 983148 983145 ( 983152 ) E X E X = ( ) sum

isin 983160

983147

R

X

983160

983147

P

X

983160

983147

983147 ( ) = 983150 ( 983081

983150

983147

983150 minus 1

983147 minus 1

( 983081

7242019 More Discrete Random Variable Solved Problems

httpslidepdfcomreaderfullmore-discrete-random-variable-solved-problems 45

First note that we can prove by the following combinatorial interpretation Suppose that

from a group of students we would like to choose a committee of students one of whom is chosen to bethe committee chair We can do this

1 by choosing people first (in ways) and then choosing one of them to be the chair ( ways) or

2 by choosing the chair first ( possibilities and then choosing students from the remaining

students (in ways))

Thus we conclude

Now lets find for

Note that the last line is true because the is equal to for a

random variable that has distribution hence it is equal to

Problem 7

Let be a discrete random variable with Prove

Solution Note that

Thus

Problem 8

If find Var

Solution

Problem 9

983147 ( ) = 983150 ( 983081

983150

983147

983150 minus 1

983147 minus 1

983150 983147

983147 ( )

983150

983147

983147

983150 983147 minus 1

983150 minus 1 ( 983081

983150 minus 1

983147 minus 1

983147 983080 983081 = 983150 983080 983081

983150

983147

983150 minus 1

983147 minus 1

E X X sim B 983145 983150 983151 983149 983145 a 983148 ( 983150 983152 )

E X = 983147 ( ) sum

983150

983147 = 0

983150

983147

983152

983147

983153

983150 minus 983147

= 983147 ( ) sum

983150

983147 = 1

983150

983147

983152

983147

983153

983150 minus 983147

= 983150 ( 983081 sum

983150

983147 = 1

983150 minus 1

983147 minus 1

983152

983147

983153

983150 minus 983147

= 983150 983152 ( 983081 sum

983150

983147 = 1

983150 minus 1

983147 minus 1

983152

983147 minus 1

983153

983150 minus 983147

= 983150 983152 ( 983081 sum

983150 minus 1

983148 = 0

983150 minus 1

983148

983152

983148

983153

( 983150 minus 1 ) minus 983148

= 983150 983152

( 983081 sum

983150 minus 1

983148 = 0

983150 minus 1

983148

983152

983148

983153

( 983150 minus 1 ) minus 983148

( 983148 ) sum

983150 minus 1

983148 = 0

P

Y

Y B 983145 983150 983151 983149 983145 a 983148 ( 983150 minus 1 983152 ) 1

X sub 0 1 2 R

X

E X = P ( X gt 983147 ) sum

983147 = 0

infin

P ( X gt 0 ) = ( 1 ) + ( 2 ) + ( 3 ) + ( 4 ) + ⋯ P

X

P

X

P

X

P

X

P ( X gt 1 ) = ( 2 ) + ( 3 ) + ( 4 ) + ⋯ P

X

P

X

P

X

P ( X gt 2 ) = ( 3 ) + ( 4 ) + ( 5 ) + ⋯ P

X

P

X

P

X

P ( X gt 983147 ) sum

infin

983147 = 0

= P ( X gt 0 ) + P ( X gt 1 ) + P ( X gt 2 ) +

= ( 1 ) + 2 ( 2 ) + 3 ( 3 ) + 4 ( 4 ) + P

X

P

X

P

X

P

X

= E X

X sim P 983151 983145 983155 983155 983151 983150 ( λ ) ( X )

( 2 minus ) = 6

7242019 More Discrete Random Variable Solved Problems

httpslidepdfcomreaderfullmore-discrete-random-variable-solved-problems 55

Let and be two independent random variables Suppose that we know Var and Var

Find Var and Var

Solution

Lets first make sure we understand what Var and Var mean They are Var and

Var where the random variables and are defined as and

Since and are independent random variables then and are independent random variables

Also and are independent random variables Thus by using Equation 37 we can write

By solving for Var and Var we obtain Var and Var

larr previousnext rarr

X Y ( 2 X minus Y ) = 6

( X + 2 Y ) = 9 ( X ) ( Y )

( 2 X minus Y ) ( X + 2 Y ) ( Z )

( W ) Z W Z = 2 X minus Y W = X + 2 Y

X Y 2 X minus Y

X 2 Y

V a r ( 2 X minus Y ) = V a r ( 2 X ) + V a r ( - Y ) = 4 V a r ( X ) + V a r ( Y ) = 6

V a r ( X + 2 Y ) = V a r ( X ) + V a r ( 2 Y ) = V a r ( X ) + 4 V a r ( Y ) = 9

( X ) ( Y ) ( X ) = 1 ( Y ) = 2

Page 2: More Discrete Random Variable Solved Problems

7242019 More Discrete Random Variable Solved Problems

httpslidepdfcomreaderfullmore-discrete-random-variable-solved-problems 25

c Again using LOTUS we have

Problem 3

Let be a discrete random variable with PMF

Define Find the PMF of

Solution

First note that Thus

Thus

Problem 4

Let Find

Solution

The PMF of is given by

where Thus

V a r ( X ) = ( 3 4 ) minus ( 1 6 = 0 8 4 )

2

E ( X minus 2 = ( 0 minus 2 ( 0 1 ) + ( 1 minus 2 ( 0 4 ) + ( 2 minus 2 ( 0 3 ) + ( 3 minus 2 ( 0 2 ) = 1 )

2

)

2

)

2

)

2

)

2

X

( 983147 ) = P

X

0 2

0 2

0 3

0 3

0

f o r 983147 = 0

f o r 983147 = 1

f o r 983147 = 2

f o r 983147 = 3

o t h e r w i s e

Y = X ( X minus 1 ) ( X minus 2 ) Y

= 983160 ( 983160 minus 1 ) ( 983160 minus 2 ) | 983160 isin 0 1 2 3 = 0 6 R

Y

( 0 ) P

Y

= P ( Y = 0 ) = P ( ( X = 0 ) o r ( X = 1 ) o r ( X = 2 ) )

= ( 0 ) + ( 1 ) + ( 2 ) P

X

P

X

P

X

= 0 7

( 6 ) P

Y

= P ( X = 3 ) = 0 3

( 983147 ) = P

Y

0 7

0 3

0

f o r 983147 = 0

f o r 983147 = 6

o t h e r w i s e

X sim G 983141 983151 983149 983141 983156 983154 983145 c ( 983152 ) E 983131 983133

1

2

X

X

( 983147 ) = 983163 P

X

983152 983153

983147 minus 1

0

f o r 983147 = 1 2 3

o t h e r w i s e

983153 = 1 minus 983152

E 983131 983133

1

2

X

= ( 983147 ) sum

infin

983147 = 1

1

2

983147

P

X

= 983152 sum

infin

983147 = 1

1

2

983147

983153

983147 minus 1

=

983152

2

sum

infin

983147 = 1

( 983081

983153

2

983147 minus 1

=

983152

2

1

1 minus

983153

2

=

983152

1 + 983152

7242019 More Discrete Random Variable Solved Problems

httpslidepdfcomreaderfullmore-discrete-random-variable-solved-problems 35

Problem 5

If find

Solution

The PMF of is given by

where

Finding directly seems to be very complicated So lets try to see if we can find an easier way to find

In particular a powerful tool that we have is linearity of expectation Can we write as the sum of

simpler random variables To do so lets remember the random experiment behind the hypergeometric

distribution You have a bag that contains blue marbles and red marbles You choose marblesat random (without replacement) and let be the number of blue marbles in your sample In particular lets

define the indicator random variables as follows

Then we can write

Thus

To find we note that for any particular all marbles are equally likely to be chosen This is

because of symmetry no marble is more likely to be chosen than the th marble as any other marblesTherefore

We conclude

Thus we have

Problem 6

In Example 314 we showed that if then We found this by writing as the sum

of random variables Now find directly using Hint Use

Solution

X sim H 983161 983152 983141 983154 983143 983141 983151 983149 983141 983156 983154 983145 c ( b 983154 983147 ) E X

X

( 983160 ) = P

X

( 983081 ( )

b

983160

983154

983147 minus

983160

( 983081

b + 983154

983147

0

f o r 983160 isin R

X

o t h e r w i s e

= m a x ( 0 983147 minus 983154 ) m a x ( 0 983147 minus 983154 ) + 1 m a x ( 0 983147 minus 983154 ) + 2 m i n ( 983147 b ) R

X

E X

E X X

X

983145

b 983154 983147 le b + 983154

X

X

983145

= 983163 X

983145

1

0

i f t h e 983145 t h c h o s e n m a r b l e i s b l u e

o t h e r w i s e

X = + + ⋯ + X

1

X

2

X

983147

E X = E + E + ⋯ + E X

1

X

2

X

983147

P ( = 1 ) X

983145

X

983145

983145

P ( = 1 ) = f o r a l l 983145 isin 1 2 ⋯ 983147 X

983145

b

b + 983154

E X

983145

= 0 sdot 983152 ( = 0 ) + 1 sdot P ( = 1 ) X

983145

X

983145

=

b

b + 983154

E X =

983147 b

b + 983154

X sim B 983145 983150 983151 983149 983145 a 983148 ( 983150 983152 ) E X = 983150 983152 X

983150 B 983141 983154 983150 983151 983157 983148 983148 983145 ( 983152 ) E X E X = ( ) sum

isin 983160

983147

R

X

983160

983147

P

X

983160

983147

983147 ( ) = 983150 ( 983081

983150

983147

983150 minus 1

983147 minus 1

( 983081

7242019 More Discrete Random Variable Solved Problems

httpslidepdfcomreaderfullmore-discrete-random-variable-solved-problems 45

First note that we can prove by the following combinatorial interpretation Suppose that

from a group of students we would like to choose a committee of students one of whom is chosen to bethe committee chair We can do this

1 by choosing people first (in ways) and then choosing one of them to be the chair ( ways) or

2 by choosing the chair first ( possibilities and then choosing students from the remaining

students (in ways))

Thus we conclude

Now lets find for

Note that the last line is true because the is equal to for a

random variable that has distribution hence it is equal to

Problem 7

Let be a discrete random variable with Prove

Solution Note that

Thus

Problem 8

If find Var

Solution

Problem 9

983147 ( ) = 983150 ( 983081

983150

983147

983150 minus 1

983147 minus 1

983150 983147

983147 ( )

983150

983147

983147

983150 983147 minus 1

983150 minus 1 ( 983081

983150 minus 1

983147 minus 1

983147 983080 983081 = 983150 983080 983081

983150

983147

983150 minus 1

983147 minus 1

E X X sim B 983145 983150 983151 983149 983145 a 983148 ( 983150 983152 )

E X = 983147 ( ) sum

983150

983147 = 0

983150

983147

983152

983147

983153

983150 minus 983147

= 983147 ( ) sum

983150

983147 = 1

983150

983147

983152

983147

983153

983150 minus 983147

= 983150 ( 983081 sum

983150

983147 = 1

983150 minus 1

983147 minus 1

983152

983147

983153

983150 minus 983147

= 983150 983152 ( 983081 sum

983150

983147 = 1

983150 minus 1

983147 minus 1

983152

983147 minus 1

983153

983150 minus 983147

= 983150 983152 ( 983081 sum

983150 minus 1

983148 = 0

983150 minus 1

983148

983152

983148

983153

( 983150 minus 1 ) minus 983148

= 983150 983152

( 983081 sum

983150 minus 1

983148 = 0

983150 minus 1

983148

983152

983148

983153

( 983150 minus 1 ) minus 983148

( 983148 ) sum

983150 minus 1

983148 = 0

P

Y

Y B 983145 983150 983151 983149 983145 a 983148 ( 983150 minus 1 983152 ) 1

X sub 0 1 2 R

X

E X = P ( X gt 983147 ) sum

983147 = 0

infin

P ( X gt 0 ) = ( 1 ) + ( 2 ) + ( 3 ) + ( 4 ) + ⋯ P

X

P

X

P

X

P

X

P ( X gt 1 ) = ( 2 ) + ( 3 ) + ( 4 ) + ⋯ P

X

P

X

P

X

P ( X gt 2 ) = ( 3 ) + ( 4 ) + ( 5 ) + ⋯ P

X

P

X

P

X

P ( X gt 983147 ) sum

infin

983147 = 0

= P ( X gt 0 ) + P ( X gt 1 ) + P ( X gt 2 ) +

= ( 1 ) + 2 ( 2 ) + 3 ( 3 ) + 4 ( 4 ) + P

X

P

X

P

X

P

X

= E X

X sim P 983151 983145 983155 983155 983151 983150 ( λ ) ( X )

( 2 minus ) = 6

7242019 More Discrete Random Variable Solved Problems

httpslidepdfcomreaderfullmore-discrete-random-variable-solved-problems 55

Let and be two independent random variables Suppose that we know Var and Var

Find Var and Var

Solution

Lets first make sure we understand what Var and Var mean They are Var and

Var where the random variables and are defined as and

Since and are independent random variables then and are independent random variables

Also and are independent random variables Thus by using Equation 37 we can write

By solving for Var and Var we obtain Var and Var

larr previousnext rarr

X Y ( 2 X minus Y ) = 6

( X + 2 Y ) = 9 ( X ) ( Y )

( 2 X minus Y ) ( X + 2 Y ) ( Z )

( W ) Z W Z = 2 X minus Y W = X + 2 Y

X Y 2 X minus Y

X 2 Y

V a r ( 2 X minus Y ) = V a r ( 2 X ) + V a r ( - Y ) = 4 V a r ( X ) + V a r ( Y ) = 6

V a r ( X + 2 Y ) = V a r ( X ) + V a r ( 2 Y ) = V a r ( X ) + 4 V a r ( Y ) = 9

( X ) ( Y ) ( X ) = 1 ( Y ) = 2

Page 3: More Discrete Random Variable Solved Problems

7242019 More Discrete Random Variable Solved Problems

httpslidepdfcomreaderfullmore-discrete-random-variable-solved-problems 35

Problem 5

If find

Solution

The PMF of is given by

where

Finding directly seems to be very complicated So lets try to see if we can find an easier way to find

In particular a powerful tool that we have is linearity of expectation Can we write as the sum of

simpler random variables To do so lets remember the random experiment behind the hypergeometric

distribution You have a bag that contains blue marbles and red marbles You choose marblesat random (without replacement) and let be the number of blue marbles in your sample In particular lets

define the indicator random variables as follows

Then we can write

Thus

To find we note that for any particular all marbles are equally likely to be chosen This is

because of symmetry no marble is more likely to be chosen than the th marble as any other marblesTherefore

We conclude

Thus we have

Problem 6

In Example 314 we showed that if then We found this by writing as the sum

of random variables Now find directly using Hint Use

Solution

X sim H 983161 983152 983141 983154 983143 983141 983151 983149 983141 983156 983154 983145 c ( b 983154 983147 ) E X

X

( 983160 ) = P

X

( 983081 ( )

b

983160

983154

983147 minus

983160

( 983081

b + 983154

983147

0

f o r 983160 isin R

X

o t h e r w i s e

= m a x ( 0 983147 minus 983154 ) m a x ( 0 983147 minus 983154 ) + 1 m a x ( 0 983147 minus 983154 ) + 2 m i n ( 983147 b ) R

X

E X

E X X

X

983145

b 983154 983147 le b + 983154

X

X

983145

= 983163 X

983145

1

0

i f t h e 983145 t h c h o s e n m a r b l e i s b l u e

o t h e r w i s e

X = + + ⋯ + X

1

X

2

X

983147

E X = E + E + ⋯ + E X

1

X

2

X

983147

P ( = 1 ) X

983145

X

983145

983145

P ( = 1 ) = f o r a l l 983145 isin 1 2 ⋯ 983147 X

983145

b

b + 983154

E X

983145

= 0 sdot 983152 ( = 0 ) + 1 sdot P ( = 1 ) X

983145

X

983145

=

b

b + 983154

E X =

983147 b

b + 983154

X sim B 983145 983150 983151 983149 983145 a 983148 ( 983150 983152 ) E X = 983150 983152 X

983150 B 983141 983154 983150 983151 983157 983148 983148 983145 ( 983152 ) E X E X = ( ) sum

isin 983160

983147

R

X

983160

983147

P

X

983160

983147

983147 ( ) = 983150 ( 983081

983150

983147

983150 minus 1

983147 minus 1

( 983081

7242019 More Discrete Random Variable Solved Problems

httpslidepdfcomreaderfullmore-discrete-random-variable-solved-problems 45

First note that we can prove by the following combinatorial interpretation Suppose that

from a group of students we would like to choose a committee of students one of whom is chosen to bethe committee chair We can do this

1 by choosing people first (in ways) and then choosing one of them to be the chair ( ways) or

2 by choosing the chair first ( possibilities and then choosing students from the remaining

students (in ways))

Thus we conclude

Now lets find for

Note that the last line is true because the is equal to for a

random variable that has distribution hence it is equal to

Problem 7

Let be a discrete random variable with Prove

Solution Note that

Thus

Problem 8

If find Var

Solution

Problem 9

983147 ( ) = 983150 ( 983081

983150

983147

983150 minus 1

983147 minus 1

983150 983147

983147 ( )

983150

983147

983147

983150 983147 minus 1

983150 minus 1 ( 983081

983150 minus 1

983147 minus 1

983147 983080 983081 = 983150 983080 983081

983150

983147

983150 minus 1

983147 minus 1

E X X sim B 983145 983150 983151 983149 983145 a 983148 ( 983150 983152 )

E X = 983147 ( ) sum

983150

983147 = 0

983150

983147

983152

983147

983153

983150 minus 983147

= 983147 ( ) sum

983150

983147 = 1

983150

983147

983152

983147

983153

983150 minus 983147

= 983150 ( 983081 sum

983150

983147 = 1

983150 minus 1

983147 minus 1

983152

983147

983153

983150 minus 983147

= 983150 983152 ( 983081 sum

983150

983147 = 1

983150 minus 1

983147 minus 1

983152

983147 minus 1

983153

983150 minus 983147

= 983150 983152 ( 983081 sum

983150 minus 1

983148 = 0

983150 minus 1

983148

983152

983148

983153

( 983150 minus 1 ) minus 983148

= 983150 983152

( 983081 sum

983150 minus 1

983148 = 0

983150 minus 1

983148

983152

983148

983153

( 983150 minus 1 ) minus 983148

( 983148 ) sum

983150 minus 1

983148 = 0

P

Y

Y B 983145 983150 983151 983149 983145 a 983148 ( 983150 minus 1 983152 ) 1

X sub 0 1 2 R

X

E X = P ( X gt 983147 ) sum

983147 = 0

infin

P ( X gt 0 ) = ( 1 ) + ( 2 ) + ( 3 ) + ( 4 ) + ⋯ P

X

P

X

P

X

P

X

P ( X gt 1 ) = ( 2 ) + ( 3 ) + ( 4 ) + ⋯ P

X

P

X

P

X

P ( X gt 2 ) = ( 3 ) + ( 4 ) + ( 5 ) + ⋯ P

X

P

X

P

X

P ( X gt 983147 ) sum

infin

983147 = 0

= P ( X gt 0 ) + P ( X gt 1 ) + P ( X gt 2 ) +

= ( 1 ) + 2 ( 2 ) + 3 ( 3 ) + 4 ( 4 ) + P

X

P

X

P

X

P

X

= E X

X sim P 983151 983145 983155 983155 983151 983150 ( λ ) ( X )

( 2 minus ) = 6

7242019 More Discrete Random Variable Solved Problems

httpslidepdfcomreaderfullmore-discrete-random-variable-solved-problems 55

Let and be two independent random variables Suppose that we know Var and Var

Find Var and Var

Solution

Lets first make sure we understand what Var and Var mean They are Var and

Var where the random variables and are defined as and

Since and are independent random variables then and are independent random variables

Also and are independent random variables Thus by using Equation 37 we can write

By solving for Var and Var we obtain Var and Var

larr previousnext rarr

X Y ( 2 X minus Y ) = 6

( X + 2 Y ) = 9 ( X ) ( Y )

( 2 X minus Y ) ( X + 2 Y ) ( Z )

( W ) Z W Z = 2 X minus Y W = X + 2 Y

X Y 2 X minus Y

X 2 Y

V a r ( 2 X minus Y ) = V a r ( 2 X ) + V a r ( - Y ) = 4 V a r ( X ) + V a r ( Y ) = 6

V a r ( X + 2 Y ) = V a r ( X ) + V a r ( 2 Y ) = V a r ( X ) + 4 V a r ( Y ) = 9

( X ) ( Y ) ( X ) = 1 ( Y ) = 2

Page 4: More Discrete Random Variable Solved Problems

7242019 More Discrete Random Variable Solved Problems

httpslidepdfcomreaderfullmore-discrete-random-variable-solved-problems 45

First note that we can prove by the following combinatorial interpretation Suppose that

from a group of students we would like to choose a committee of students one of whom is chosen to bethe committee chair We can do this

1 by choosing people first (in ways) and then choosing one of them to be the chair ( ways) or

2 by choosing the chair first ( possibilities and then choosing students from the remaining

students (in ways))

Thus we conclude

Now lets find for

Note that the last line is true because the is equal to for a

random variable that has distribution hence it is equal to

Problem 7

Let be a discrete random variable with Prove

Solution Note that

Thus

Problem 8

If find Var

Solution

Problem 9

983147 ( ) = 983150 ( 983081

983150

983147

983150 minus 1

983147 minus 1

983150 983147

983147 ( )

983150

983147

983147

983150 983147 minus 1

983150 minus 1 ( 983081

983150 minus 1

983147 minus 1

983147 983080 983081 = 983150 983080 983081

983150

983147

983150 minus 1

983147 minus 1

E X X sim B 983145 983150 983151 983149 983145 a 983148 ( 983150 983152 )

E X = 983147 ( ) sum

983150

983147 = 0

983150

983147

983152

983147

983153

983150 minus 983147

= 983147 ( ) sum

983150

983147 = 1

983150

983147

983152

983147

983153

983150 minus 983147

= 983150 ( 983081 sum

983150

983147 = 1

983150 minus 1

983147 minus 1

983152

983147

983153

983150 minus 983147

= 983150 983152 ( 983081 sum

983150

983147 = 1

983150 minus 1

983147 minus 1

983152

983147 minus 1

983153

983150 minus 983147

= 983150 983152 ( 983081 sum

983150 minus 1

983148 = 0

983150 minus 1

983148

983152

983148

983153

( 983150 minus 1 ) minus 983148

= 983150 983152

( 983081 sum

983150 minus 1

983148 = 0

983150 minus 1

983148

983152

983148

983153

( 983150 minus 1 ) minus 983148

( 983148 ) sum

983150 minus 1

983148 = 0

P

Y

Y B 983145 983150 983151 983149 983145 a 983148 ( 983150 minus 1 983152 ) 1

X sub 0 1 2 R

X

E X = P ( X gt 983147 ) sum

983147 = 0

infin

P ( X gt 0 ) = ( 1 ) + ( 2 ) + ( 3 ) + ( 4 ) + ⋯ P

X

P

X

P

X

P

X

P ( X gt 1 ) = ( 2 ) + ( 3 ) + ( 4 ) + ⋯ P

X

P

X

P

X

P ( X gt 2 ) = ( 3 ) + ( 4 ) + ( 5 ) + ⋯ P

X

P

X

P

X

P ( X gt 983147 ) sum

infin

983147 = 0

= P ( X gt 0 ) + P ( X gt 1 ) + P ( X gt 2 ) +

= ( 1 ) + 2 ( 2 ) + 3 ( 3 ) + 4 ( 4 ) + P

X

P

X

P

X

P

X

= E X

X sim P 983151 983145 983155 983155 983151 983150 ( λ ) ( X )

( 2 minus ) = 6

7242019 More Discrete Random Variable Solved Problems

httpslidepdfcomreaderfullmore-discrete-random-variable-solved-problems 55

Let and be two independent random variables Suppose that we know Var and Var

Find Var and Var

Solution

Lets first make sure we understand what Var and Var mean They are Var and

Var where the random variables and are defined as and

Since and are independent random variables then and are independent random variables

Also and are independent random variables Thus by using Equation 37 we can write

By solving for Var and Var we obtain Var and Var

larr previousnext rarr

X Y ( 2 X minus Y ) = 6

( X + 2 Y ) = 9 ( X ) ( Y )

( 2 X minus Y ) ( X + 2 Y ) ( Z )

( W ) Z W Z = 2 X minus Y W = X + 2 Y

X Y 2 X minus Y

X 2 Y

V a r ( 2 X minus Y ) = V a r ( 2 X ) + V a r ( - Y ) = 4 V a r ( X ) + V a r ( Y ) = 6

V a r ( X + 2 Y ) = V a r ( X ) + V a r ( 2 Y ) = V a r ( X ) + 4 V a r ( Y ) = 9

( X ) ( Y ) ( X ) = 1 ( Y ) = 2

Page 5: More Discrete Random Variable Solved Problems

7242019 More Discrete Random Variable Solved Problems

httpslidepdfcomreaderfullmore-discrete-random-variable-solved-problems 55

Let and be two independent random variables Suppose that we know Var and Var

Find Var and Var

Solution

Lets first make sure we understand what Var and Var mean They are Var and

Var where the random variables and are defined as and

Since and are independent random variables then and are independent random variables

Also and are independent random variables Thus by using Equation 37 we can write

By solving for Var and Var we obtain Var and Var

larr previousnext rarr

X Y ( 2 X minus Y ) = 6

( X + 2 Y ) = 9 ( X ) ( Y )

( 2 X minus Y ) ( X + 2 Y ) ( Z )

( W ) Z W Z = 2 X minus Y W = X + 2 Y

X Y 2 X minus Y

X 2 Y

V a r ( 2 X minus Y ) = V a r ( 2 X ) + V a r ( - Y ) = 4 V a r ( X ) + V a r ( Y ) = 6

V a r ( X + 2 Y ) = V a r ( X ) + V a r ( 2 Y ) = V a r ( X ) + 4 V a r ( Y ) = 9

( X ) ( Y ) ( X ) = 1 ( Y ) = 2