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MT2504 Combinatorics and Probability Chapter 1 $8.91   Add to cart

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MT2504 Combinatorics and Probability Chapter 1

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  • August 3, 2022
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  • 2020/2021
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Sets , counting and elementary probability
CHAPTER 1

Definition :




sets A ,
B are
disjoint if A⑧ =
0 . Sets Ai ,
- - . ,An are ( pairwise)
⑦ Ai
)
disjoint if
,
Aj disjoint (
i #
j)

↳ for all
a g




Theorem : 1.5



Let A O be finite and sets then
, disjoint ,




IAU 81 =
IAI t
181


Proof :




het
A =
{ a
, .az ,
-
- -


,
am } for some M n EIN
,

B =
{ b. ,
bz
,
- - .

,
bn }


AUB - { a
, .ae . . . .

,
am
,
bi
,
bz ,
-
-
-




,
bn }


↳ Because ( sets disjoint) ( Au ol IA It 181
repetition are hence Mtn
'

no
-

: - -




,




theorem : 1.8



Az , . . .
,
An pairwise disjoint finite sets .




I A. U .
. .

VANI =
IA It ,
-
- - t
tant =
Eh ,
tail
Proof -
.




induction ( already done n 2) → Theorem 's
By
-



on n
-


.




suppose true for n > 2 .
Let Az ,
-
. .


,
Anti disjoint finite sets be given .




Set A =
Aau . . -
VAN


since An Ant , =
( Ain Anti) = ¢ since all Ai are pairwise disjoint .




A and Ant ,
'



are
disjoint
-
'




By inductive (a )
hypothesis z
-
:
-




IAU And =
( Alt ( Ant il
REMEMBER :
IAI =
I Aa U . .
-
U Ant = IA , It - - - t ( Anl
SO
,




I Azu . . . U Ant I ,
= ( Alt l Anti ) =
( Att - - -
t
tant I ,

, Observations :




Let A. 8 be sets


IAI 30 ( ( Al o ⇐>
A 0 )
-



• -
=




•• A EB IAI ← 101 B = AUB LA → A ,
8 disjoint


Az ,
.
. .

,
An disjoint if Ail ,
=
is ,
I Ail

Definition ( 2.1 )


let r be a finite sample space :




A probability IP : → IR
assigns every event a number s - t :




→ Collection of all subsets of R



AXIOM 1 : ( non -




negativity ) VA Os PLA ) EI




AXIOM 2 : ( honesty) ( pls) -

-
1




AXIOM 3 : ( additivity) Az ,
. .
.

,
An disjoint PCA , U . . .
Van ) =
i. MAI )

Definition X. 3)


If IP is a
probability on r
,
the function f : r → IR
,
f- ( w ) =
BLEW } ) is


the
probability mass function of IP .




Lemma ( 2.4 )


het r =
{ wi }? , ,
IP
probability so that each outcome is
equally likely .
Then
,




Ant IAI
'
✓ events A Er IRA ) =
=



,
Irl

proof :




flw ) t Er To
compute p
:
w
p
-
-


.




Is D= It )
>
1 :
Ip ( r) =


,
flwi ) =
rip ,
{ wi } IP ( { wi } -
-

Hwi)
,
-
-

Honesty Additivity
so
p
-

-
ht

Now let A er be
given ,




Ant
'
IPCA ) =
Efcw) =
Http =


WEA


↳ sum over elements of A

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