ISI MStat PSB 2007 Problem 6 | Counting Principle & Expectations

This is a very beautiful sample problem from ISI MStat PSB 2007 Problem 6 based on counting principle . Let's give it a try !!

Problem- ISI MStat PSB 2007 Problem 6

18 boys and 2 girls are made to stand in a line in a random order. Let \(X\) be the number of boys standing in between the girls. Find
(a) P(X=5)
(b) \( E(X) \)


Prerequisites


Basic Counting Principle

Probability

Discrete random variable

Solution :

If there are j boys in between 2 girls then first we have to choose j boys out of 18 boys in \( {18 \choose j} \) ways now this j boys can arrange among themselves in j! ways and 2 girls can arrange among themselves in 2! ways and now consider these j boys and 2 girls as a single person then this single person along with remaining (18-j) boys can arrange among themselves in (18-j+1)! ways .

Giving all total \( 2! {18 \choose j} j! (18-j+1)! \) possible arrangements .

Again without any restrictions there are (18+2)!=20! arrangements .

Hence \( P(X=j)=\frac{ 2! {18 \choose j} j! (18-j+1)! }{20!} = \frac{19-j}{190} \)

(a) \( P(X=5)=\frac{19-5}{190}=\frac{7}{95} \)

(b) \( E(X)= \sum_{j=0}^{18} \frac{j (19-j )}{190} = 9 \) just computing the sum of first 18 natural number and sum of squares of first 18 natural numbes.


Food For Thought

Find the same under the condition that 18 boys and 2 girls sit in a circular table in a random order .


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ISI MStat PSB 2006 Problem 6 | Counting Principle & Expectations

This is a very beautiful sample problem from ISI MStat PSB 2006 Problem 6 based on counting principle . Let's give it a try !!

Problem- ISI MStat PSB 2006 Problem 6


Let \( Y_{1}, Y_{2}, Y_{3}\) be i.i.d. continuous random variables. For i=1,2, define \( U_{i}\) as

\( U_{i}= \begin{cases} 1 , & Y_{i+1}>Y_{i} \\ 0 , & \text{otherwise} \end{cases} \)
Find the mean and variance of \( U_{1}+U_{2}\) .

Prerequisites


Basic Counting Principle

Probability

Continuous random variable

Solution :

\( E(U_1+U_2)=E(U_1)+E(U_2)\)

Now \( E(U_1)=1 \times P(Y_2>Y_1) = \frac{1}{2} \), as there are only two cases either \( Y_2>Y_1\) or \( Y_2<Y_1 \).

Similarly , \( E(U_2)= \frac{1}{2} \)

So, \( E(U_1+U_2)= 1 \)

\( Var(U_1+U_2)=Var(U_1)+Var(U_2)+2Cov(U_1,U_2) \) .

\( Var(U_1)=E({U_1}^2)-{E(U_1)}^2=1^2 \times P(Y_2>Y_1) - {\frac{1}{2}}^2 = \frac{1}{2}-\frac{1}{4}=\frac{1}{4} \)

Similarly ,\( Var(U_2)=\frac{1}{4} \)

\( Cov(U_1,U_2)=E(U_1 U_2)-E(U_1)E(U_2)=1 \times P(Y_3>Y_2>Y_1) - {\frac{1}{2}}^2 = \frac{1}{3!}-{\frac{1}{2}}^2 \) ( as there are 3! possible arrangements of \(Y_i's\) keeping inequalities fixed .

Therefore , \( Var(U_1+U_2) = 2 \times \frac{1}{4} + 2 \times (\frac{1}{6}- \frac{1}{4}) = \frac{1}{3} \)


Food For Thought

Find the same under the condition that \( Y_i's\) are iid poission random variables .


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ISI MStat PSB 2006 Problem 5 | Binomial Distribution

This is a very beautiful sample problem from ISI MStat PSB 2006 Problem 5 based on use of binomial distribution . Let's give it a try !!

Problem- ISI MStat PSB 2006 Problem 5


Suppose \(X\) is the number of heads in 10 tossses of a fair coin. Given \( X=5,\) what is the probability that the first head occured in the third toss?

Prerequisites


Basic Counting Principle

Conditional Probability

Binomial Distribution

Solution :

As \(X\) is the number of heads in 10 tossses of a fair coin so \( X \sim binom(10, \frac{1}{2} ) \)

A be the event that first head occured in third toss

B be the event that X=5

We have to find that \( P(A|B)=\frac{P(A \cap B)}{P(B)} = \frac{ {7 \choose 4} {\frac{1}{2}}^{10} }{ {10 \choose 5} {\frac{1}{2}}^{10}} \)

As , \( P(A \cap B) \) = Probability that out of 5 heads occur at 10 tosses 1st head occur at 3rd throw

=Probability that first two tails \( \times \) probability that 3rd one is head \( \times \) probability that out of 7 toss 4 toss will give head

= \( {\frac{1}{2}}^2 \times \frac{1}{2} \times {7 \choose 4} {\frac{1}{2}}^{7} \)

Hence our required probability is \( \frac{5}{36} \)


Food For Thought

Under the same condition find the probability that X= 3 given 1st head obtained from 2nd throw .


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ISI MStat PSB 2005 Problem 2 | Calculating probability using Binomial Distribution

This is a very beautiful sample problem from ISI MStat PSB 2005 Problem 2 based on finding probability using the binomial distribution. Let's give it a try !!

Problem- ISI MStat PSB 2005 Problem 2


Let \(X\) and \(Y\) be independent random variables with X having a binomial distribution with parameters 5 and \(1 / 2\) and \(Y\) having a binomial distribution with parameters 7 and \(1 / 2 .\) Find the probability that \(|X-Y|\) is even.

Prerequisites


Binomial Distribution

Binomial Expansion

Parity Check

Solution :

Given \( X \sim \) Bin(5,1/2) and \( Y \sim \) Bin(7,1/2) , and they are independent .

Now , we have to find , \( P(|X-Y|=even ) \)

\( |X-Y| \)= even if both X and Y are even or both X and Y are odd .

Therefore \( P(|X-Y|=even )=P(X=even,Y=even) + P(X=odd , Y=odd) \)

P(X=even , Y= even ) =\( ( {5 \choose 0} {(\frac{1}{2})}^5 + {5 \choose 2} {(\frac{1}{2})}^5 + \cdots + {5 \choose 4} {(\frac{1}{2})}^5 )( {7 \choose 0} {(\frac{1}{2})}^7 + {7 \choose 2} {(\frac{1}{2})}^7 + \cdots + {7 \choose 6} {(\frac{1}{2})}^7)\)

=\( ({(\frac{1}{2})}^5 \times \frac{2^5}{2})({(\frac{1}{2})}^7 \times \frac{2^7}{2}) \)

= \(\frac{1}{4} \)

Similarly , one can find P(X=odd , Y=odd ) which is coming out to be \( \frac{1}{4} \) .

Hence , P(|X-Y|) = 14+1/4 = 1/2 .


Food For Thought

Try to find P(X-Y=odd) under the same condition as given in the above problem .


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ISI MStat PSB 2013 Problem 10 | Balls-go-round

This is a very beautiful sample problem from ISI MStat PSB 2013 Problem 10. It's based mainly on counting and following the norms stated in the problem itself. Be careful while thinking !

Problem- ISI MStat PSB 2013 Problem 10


There are 10 empty boxes numbered 1,2,......,10 placed sequentially on a circle as shown in the figure,

We perform 100 independent trials. At each trial one box is selected with probability \(\frac{1}{10}\) and a ball is placed in each of the two neighboring boxes of the selected one.

Define \(X_k\) be the number of balls in the \(k^{th}\) box at the end of 100 trials.

(a) Find \(E(X_k)\) for \( 1 \le k \le 10\).

(b) Find \(Cov(X_k, X_5)\) for \(1 \le k \le 10 \).

Prerequisites


Counting principles

Binomial Distribution

Independence of Events

Solution :

At first this problem may seem a bit of complex, but when one get to see the pattern it starts unfolding. For his types of problem, I find a useful technique is to follow the picture, in this case the picture is being provided, (if not draw it yourself !!)

Given, \(X_k\) : # balls in the \(k^{th}\) box at the end of 100 trials.

So, the possible values of \(X_k\) are 0,1,2,.....,100. and the probability that at the jth trial a ball will added to the kth box is \(\frac{1}{10}\) , (why??) .

Now, \(P(X_k=x)\)= \({100 \choose x}\)\( (\frac{1}{5})^{x}\) \( (\frac{4}{5})^{100-x} \) \( x=0,1,......,100\)

Clearly, \( X_k \sim binomial( 100, \frac{1}{5})\), from here one can easily find out the the expectation of \(X_k\). But have you thought like this ??

Now, notice that after every slelection of box, 2 balls are added in the system, so at the end of the 10th trial, there will be 200 balls distributed in the system.

So, \(X_1 +X_2 +.......+ X_{100} =200 \), which implies \( \sum_{k} E(X_k)=200\), due to symmetry \(E(X_k)=E(X_l) \forall k \neq l \), So, \(E(X_k)=20\).

(b) Now this part is the cream of this problem, first notice that number of balls in kth box, is dependent on the number of balls in the (k-2)th and (k+2)th box, and vice versa, So, \(Cov( X_k, X_l)=0\) if \(|k-l|\neq 2\).

So, \(Cov(X_k, X_5)= 0 \forall k \neq 3,5 \&\ 7 \), so we just need to find the \(Cov(X_7,X_5)\) and \(Cov(X_3,X_5)\), and \(Cov(X_5,X_5)=Var(X_5)\) .

Now it is sufficient to find the covariance of any of the the above mentioned covariances, as both are symmetric and identical to each other. But for the finding say \(Cov(X_3,X_5)\), lets look whats happening in each trial more closely,

let, \(X_k= i_{k_1} +i_{k_2}+......+i{k_{100}} \) where , \( i_{k_j} = \begin{cases} 1 & if\ a\ ball\ added\ to\ the\ kth\ box\ at\ the\ jth\ trial\ \\ 0 & otherwise \end{cases}\)

So, clearly, \(P(i_{k_j}=1)=\frac{1}{5} \) ; j=1,2,....,100.

So, \(Cov(X_3,X_5)=Cov( i_{3_1}+i_{3_2}+.....+i_{3_{100}},i_{5_1}+i_{5_2}+....+i_{5_{100}})=\sum_{j=1}^{100} Cov(i_{3_j},i_{5_j})\), [\(Cov(i_{3_j},i_{5_j*})=0 \forall j\neq j*\), why ?? ].

So, \(Cov(X_3,X_5)= 100 Cov(i_{3_1},i_{5_1})=100( E(i_{3_1}i_{5_1})-E(i_{3_1})E(i_{5_1}))=100(P(i_{3_1}=1, i_{5_1}=1)-P(i_{3_1}=1)P(i_{5_1}=1))=100(\frac{1}{10}- \frac{1}{5}\frac{1}{5})=6\).

similarly, \(Cov(X_7,X_5)=6\) also, and its easy to find \(Var(X_5)\) , so I leave it as an exercise. So, \(Cov(X_k,X_5)= \begin{cases} 6 & k=3,7 \\ Var(X_5) & k=5 \\ 0 & k\neq 3,5 \or\ 7\end{cases}\). Hence we are done !!


Food For Thought

Wait, lets imagine, these boxes are interchanged in such a way that the hth box is replaced with the kth (\(\neq h\)) box, this has been done for all possible pairs of (h,k), Now can you show that all there are precisely \( 10!\sum_{i+2j=10}(i!j!2^j)^{-1}\) number of arrangements possible ?

Now imagine, in a game there are 1 balls each in every box( boxes are arranged identically as shown in the question), you pick up the ball from the first box and put it into the 2nd one, now you can't take out any ball from a box in which you just put a ball, so you pick a ball from the 3rd box and put it into the 4th and you go on like this, taking a ball frim the ith box and put it into the (i+1)th box, but cant empty the box you just filled. Now, again after the first round you remove the empty boxes and do the same thing again and again, till all the balls are not accumulated in a single box. Which box you think will contain all the balls after you run this process finitely many time ?? If you are in this lottery and you are to choose a bix before this game begin, which box you must choose ??

if the coordinator of the game, starts with any ith box how should your strategy change ?? Give it a thought !!

For help, look for Josephus Problem, you may be moved by it's beauty !


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