Don't keep us apart!

Using 2 white dots, I mark 2 points uniformly at random on a rod. Then, I choose 9 points uniformly at random on the rod, and break the rod at those points to get 10 small pieces.

To 3 decimal places, what is the probability that the 2 dots will lie on the same piece?


The answer is 0.182.

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6 solutions

Consider any 11 marks alone the rod, 9 of which indicate the break points and the other 2 being the marked points. Then of the ( 11 9 ) = 55 \dbinom{11}{9} = 55 ways these marks can be ordered, 10 10 have the 2 marked points being adjacent. As there is a one-to-one correspondence between these orderings and the outcomes specified by the question at hand, the desired probability is

p = 10 55 = 2 11 0.182 p = \dfrac{10}{55} = \dfrac{2}{11} \approx 0.182 .

In general, with 2 points on a rod broken into n n pieces, the desired probability is 2 n + 1 \dfrac{2}{n + 1} .

Moderator note:

Sometimes, reinterpreting the probability distribution would allow us to do a much simpler calculation. This is a fanciful way to apply the idea behind the Law of Iterated Expectation .

We know that E [ X ] = E ( E ( X Y ) ) \mathbb{E}[X] = \mathbb{E}(\mathbb{E}(X|Y)) . If E ( X Y ) \mathbb{E} ( X | Y ) is a constant, then it is equal to E [ X ] E[X] , regardless of the underlying distribution.

With an (assumed) independent uniform distribution for the location of each mark on the rod, is it obvious enough to assume (without comment) that any two permutations of the order of marks are equiprobable?

Mark Hennings - 4 years, 2 months ago

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That's a valid concern with such "probability reinterpretations", especially we know how much the interpretation of randomness matters. E.g. Randomly choosing 2 marks on a rod, is not equal to randomly choosing 1 mark on a rod and then randomly choosing 1 mark on the left side of the rod.

But otherwise, we're using the " law of iterated expectation ". (First argue that the probability the marks coincide is 0.) Show that given any 11 points on the rod, the cases where the marked points + break points coincide with these 11 points correspond to what we desire.

Calvin Lin Staff - 4 years, 2 months ago

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For the sake of clarity please add that the break points can't coincide with the marked points.

I have created the other version of this problem HERE

Ankit Kumar Jain - 4 years, 2 months ago

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@Ankit Kumar Jain The probability of that event is 0, which is why we ignore it.

Calvin Lin Staff - 4 years, 2 months ago

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@Calvin Lin Won't that add up to the sample space?

Ankit Kumar Jain - 4 years, 2 months ago

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@Ankit Kumar Jain The total probability of "white dot coincide with break point" is 0, which should be intuitively obvious.

Do you know how to prove that explicitly? One way to think about it is to calculate the probability that the "white dot and break point are d d apart", and figure out what happens as d d tends to 0. Note: It is important that we're using a (absolutely) continuous distributions, which has no discrete parts.

Calvin Lin Staff - 4 years, 2 months ago

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@Calvin Lin Sir , it would require calculus which I am not quite familiar with , so I won't be able to.

I tried to solve it by the basics.

I have posted that as a solution to the problem I have mentioned above HERE .

Please point out the errors.!

Ankit Kumar Jain - 4 years, 2 months ago

Nice solution!

Đức Tân Lâm - 4 years, 2 months ago

Nicely done.

Kris Hauchecorne - 4 years, 2 months ago
Abhishek Sinha
Mar 18, 2017

There are two sources of randomness: (1) breaking the rod into n = 10 n=10 pieces and (2) choosing two marked points independently and uniformly at random. We will analyze the entire process in this sequence. Without any loss of generality, assume that the whole length of the rod is 1 1 . If the lengths of the broken pieces are x = { x 1 , x 2 , , x n } \mathbf{x}=\{x_1,x_2, \ldots, x_n\} , then the conditional probability that the two marked points lie on the same piece is simply p x = i x i 2 , p_{|\mathbf{x}}=\sum_i x_i^2, which follows from the fact that the points are chosen independently. Now to obtain the unconditional probability, we simply take the expectation of the above expression with respect to x \mathbf{x} . p = E ( i x i 2 ) = ( a ) i E x i 2 = ( b ) n E x 1 2 , p = \mathbb{E}\big(\sum_i x_i^2 \big) \stackrel{(a)}{=} \sum_i \mathbb{E}x_i^2 \stackrel{(b)}{=} n \mathbb{E}x_1^2, where (a) follows from linearity of expectation and (b) follows from the fact that the random variables { x i } i = 1 n \{x_i\}_{i=1}^{n} have identical distributions. (note that, they are not independent- they sum to 1 1 !). All that now remains is to find the expectation of x 1 2 x_1^2 . Now observe that x 1 x_1 will be more than y y iff all n 1 n-1 boundary points of the broken pieces lie outside the initial y y length of the rod, i.e., P ( x 1 > y ) = ( 1 y ) n 1 . \mathbb{P}(x_1 >y)= (1-y)^{n-1}. Thus, E ( x 1 2 ) = 0 1 P ( x 1 2 > y ) d y = 0 1 ( 1 y ) n 1 d y = 2 n ( n + 1 ) . \mathbb{E}(x_1^2)=\int_{0}^{1}\mathbb{P}(x_1^2 >y) dy = \int_{0}^{1} (1-\sqrt{y})^{n-1} dy = \frac{2}{n(n+1)}. Hence, p = 2 n + 1 . p= \frac{2}{n+1}.

Mark Hennings
Mar 16, 2017

Alternatively, assume that the rod has length 1 1 . If the rod is marked at points 0 x , y 1 0 \le x,y \le 1 , then the n 1 n-1 break points that split the rod up into n n pieces must all lie outside the interval of length x y |x-y| between x x and y y . Thus the desired probability is 0 1 0 1 ( 1 x y ) n 1 d x d y = 2 0 1 d y 0 y ( 1 y + x ) n 1 d x = 2 0 1 d y 0 y ( 1 x ) n 1 d x = 2 n 0 1 ( 1 ( 1 y ) n ) d y = 2 n × n n + 1 = 2 n + 1 \begin{aligned} \int_0^1 \int_0^1 \big(1 - |x-y|\big)^{n-1}\,dx\,dy & = 2\int_0^1\,dy \int_0^y (1 - y + x)^{n-1}\,dx \; = \; 2\int_0^1\,dy \int_0^y (1-x)^{n-1}\,dx \\ & = \tfrac{2}{n}\int_0^1\big(1 - (1-y)^n\big)\,dy \; =\; \tfrac{2}{n} \times \tfrac{n}{n+1} \; = \; \tfrac{2}{n+1} \end{aligned} In this case, the probability is 2 11 = 0.1818 \tfrac{2}{11} = 0.1818\ldots .

Raj Mantri
Mar 30, 2017

By Trial and Error method, one can understand that there are ( n 2 ) {n \choose 2} ways for the 2 points to be in different pieces where n is number of pieces.


So, for 10 pieces there are ( 10 2 ) {10 \choose 2} = 45 ways to arrange them in 10 different pieces of the rod .

And for the 2 marks to lie on the same piece there are 10 ways for total 10 pieces.

Total Number of ways (Possible Outcomes) = 45 + 10 = 55

P = Number of Favorable Outcomes / Total Number of Possible Outcomes


P = 10 / 55 0.182 P = 10/55 ≈ 0.182

By Trial and Error method, one can understand that there are ( n 2 ) {n \choose 2} ways for the 2 points to be in different pieces where n is number of pieces.

Hmmm, it seems that you claimed that there are always ( n 2 ) { n \choose 2} ways, but is that true for all positive integers n n ? If it's true, how do you know that?

Pi Han Goh - 4 years, 2 months ago
Apoorva Singal
Apr 2, 2017

The probability is = the number of desired outcomes / total possible outcomes

There are 10 divisions. We want both dots to be on any single one. This desired outcome can happen on any of the 10 divisions. So number of desired outcomes is 10.

Total possible outcomes is the tricky part. Naming all divisions alphabetically starting from A we have ABCDEFGHIJ So arrangements of dots considering fist division can be AA, AB, AC, AD, AE, AF, AG, AH, AI and AJ. So thats 10 outcomes. We might conclude that so for all 10 divisions it should be 10 x 10= 100. But let's consider the second division B. The AB variation is already included in the first 10 outcomes. Hence we need to consider 9. For division C, both AC and BC must have been accounted for, so we consider 8. So on and so forth the total possible outcomes = 10 + 9 + 8 + 7 + 6 + 5 + 4 +3+2+1 = 55 Probability is 10/55 ≈ 0.182

Anand Raj
Mar 28, 2017

Let's assume you have already divided the rod into 10 pieces. Now for both dots to be on the same piece, Favourable methods are 10C1 and total ways to mark two dots is 10C1 + 10C2. Thus Probability is 10/55

Hmmm, I don't understand your solution. Why is there a 10C2 in your calculation?

Pi Han Goh - 4 years, 2 months ago

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