Bag containing 12 R 28 G balls. Three balls are drawn in succession without replacement.
We know that P (1st ball drawn is Red)
P(R1)=2012=53 & P(G1)=208=52
We have calculated some conditional probabilities
say P(G2∣R1)=198
What is the unconditional probability that the 2nd ball drawn in Green? i.e P(G2)
Now the event G2=R1G2G1G2
P(G2)=P(R1G2∪G1G2)
∴P(G2)=P(R1∩G2)+P(G1∩G2)
=P(G2∣R1)⋅P(R1)+P(G2∣G1)⋅P(G1)
=198×53+197×52=19×524+14=19×538=52
What is the unconditional probability that the 3rd ball drawn in Red?
Solution:
The 3rd ball can be Red in union of four disjoint events:
R1∩R2∩R3∪R1∩G2∩R3∪G1∩R2∩R3∪G1∩G2∩R3
∴P(R3)=P(R1R2R3)+P(R1G2R3)+P(G1R2R3)
+P(G1G2R3)
P(R3)=53×1911×1810+53×198×1811+52×1912×1811+52×197×1812
=5×19×181(330+264+264+168)=5×19×181026=53
Suppose you have 3 fair dice ∋P(1)=P(2)=P(3)=⋯=P(6)=61
Also you have a fake dice which has four faces as 5 & two faces as 6
You choose 1 of the four dice at random and throw it. You get a 5
(a) What is the probability of getting a 5 ?
(b) Given that you have got a 5 what is the probability that you have chosen the fake die?
(a) P(5)=P(5/ fair die )×P( fair die )
+P(5/ fake die )×P( fake die)
=61×43+32×41
=243+244=247
(b) P( chosen the fake die ∣ result is 5) ⟶ bayes’ theorem
P(A∣B)=P(B)P(A∩B)=P(B)P(B∣A)⋅P(A)
P( fake die ∣5)=P(5)P(5∩ fake die )
=P(5)P(5∣ fake die )×P( fake die )
=24732×41=122×724=74
Suppose you have 10 coins numbered 1,2,3…10. Suppose probability of getting a H in single tose of the ith coin in 10i,i=1,2,…10.
You choose a coin randomly and tose it
If the result you got in a H, what is the probability 5 that yon have chosen the 5th coin?
Let E be the event that you choose the 5th coin & B be the event that you got a H we want to compute P(E∣B). Using Bayes’ Theorem P(E∣B)=P(B)P(B∩E)=P(B)P(B∣E)×P(E)
Now P(B∣E)=105=21. 2P(E)=101 as the coin is chosen randmoly.
∴P(E∣B)=P(B)21×101=P( gating a H)
Now
P(B)=P(1stcoin∩B)+P(2d∩B)+⋯+P(10th ∩B)
=P(H∣1stcoin).P(1stcoin)+⋯+P(H∣10thcoin).P(10thcoin)
=101×101+102×101+⋯+1010×101
=1001(1+2+⋯+10)=1001×210×11=2011
∴P(E∣B)=2011201=111
Suppose a student is answering an MCQ question with 5 options of which only one is correct. Now let p be the probability that the student guesses the answer i.e he ticks randmoly & let 1−p be the probability that he knows the answer and therefore ticks correctly.
Suppose the student ticked correctly. What is the probability that he guessed the answer.
We want to compute P (guessing\ticked righting)
Let E be the event that he guessed it & B be the event that he ticked it correctly
∴P(E∣B)=P(B)P(B∣E)⋅P(E)
Now P(B∣E)=51, & P(E)=p (given)
And P(B)=P(B∣guess)⋅P(guess)+P(B∣know)⋅P(know)
=51×p+1⋅(1−p)=5p+5(1−p)=55−4P
∴P(E∣B)=5p \ 55−4P=5−4Pp
Suppose you have 3 bags A,B & C. The contents are as follows:
A:1W+2G+3R
B:2W+1G+1R
C:4W+5G+3R.
You choose a bag at random & take out two balls from it. Suppose you get 1W & 1R ball. What is the probability that you have choose Bag A.?
Let E be the event of selecting bag A.
B be the event of getting 1W+1R.
We want to compute P(E∣B)
Using Bayers’ Theorem: P(E∣B)=P(B)P(B∣E)⋅P(E)
Now P(E)=31 and P(B∣E)=6c23=2!4!6!3
=25×63=51.
Similary ,P(1W+1R∣BagB)2=4c22=2!2!4!2=62=31
P(1W+1R∣BagC)=12c212=211×1212=112
∴P(B)=P(1W+1R)
=51×31+31×31+31×112
=31(51+31+112)=31(16533+55+30)
=31×165118
∴P(E∣B)=31×16511851×31=51×118165=11833
Suppose you are waiting for a letter from KOLKATA, KATHMANDU and MUSCAT.
Suppose you receive a letter and the only thing legible in the address is two successive letters: AT
What is the probability that it is from KOLKATA?
P(KOLKATA∣AT)=P(AT)P(AT∣ KOLKATA )×P(KOLKATA)
Now
P(AT∣ KOLKATA) :61
P(AT∣ KATHMANDU):81
P(AT∣ MUSCAT) =51
P(KOLKATA∣AT)=61×31+81×31+51×3161×31
=61+81+5161=5×6×840+30+4861
=40+30+4840=11840=5920
Suppose India & Australia are playing a five -match test series. Suppose Virat Kohli won the toss in the first four matches.
What is the probability that he will win the toss in the fifth match as well?
(A) 1
(B) 51
(B) 5
(C) 0
(D) 21
We assume that the toss is done using an unbiased coin, so that in each toss the probability of winning is equal for both the captain.
Can it be 1? Because since Virat won all the previous tosses, therefore he will win the fifth toss.
Can it be 51 ?
Because Virat won all the 4 toss therefore now the Australia captain will have 54 probability of winning.
Can it be 0 ?
Because now Australia captain will have to win tho toss.
∴P (Virat winning) =0
Correct option is (D). ie Answer is 21 P (Virat winning 5th toss ∣ he won all the previous tosses) in same as P (Virat winning the toss) as these are independent event.