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A French-suited cards pack consist of $52$ cards where $13$ are clovers. $4$ players play a game where every player has $13$ cards in his/her hands (, in other words the full pack has been shared). Let $X$ denotes a random variable, which shows the number of players who's got at least $1$ clover. After shuffling, every outcome has the same probability. How can I calculate $\mathbf{P}\left(X=1\right)$, $\mathbf{P}\left(X=2\right)$, $\mathbf{P}\left(X=3\right)$ and $\mathbf{P}\left(X=4\right)$?

My idea was the following...

I listed all the possible outcomes:

When we calculate $\mathbf{P}\left(X=1\right)$, then one player has all the clovers, so there are $13-0-0-0$ clovers in the different packs.

When I want to calculate $\mathbf{P}\left(X=2\right)$, then there are the following cases: $12-1-0-0$, $11-2-0-0$, $10-3-0-0$, $9-4-0-0$, $8-5-0-0$, $7-6-0-0$.

In the case of $\mathbf{P}\left(X=3\right)$, the following cases can occur: $11-1-1-0$, $10-2-1-0$, $9-3-1-0$, $9-2-2-0$, $8-4-1-0$, $8-3-2-0$, $7-5-1-0$, $7-4-2-0$, $7-3-3-0$, $6-6-1-0$, $6-5-2-0$, $6-4-3-0$, $5-5-3-0$, $5-4-4-0$.

I know the previous $3$ probabilities determinates $\mathbf{P}\left(X=4\right)$, but for the sake of completeness: $10-1-1-1$, $9-2-1-1$, $8-3-1-1$, $8-2-2-1$, $7-4-1-1$, $7-3-2-1$, $7-2-2-2$, $6-5-1-1$, $6-4-2-1$, $6-3-3-1$, $6-3-2-2$, $5-5-2-1$, $5-4-3-1$, $5-4-2-2$, $5-3-3-2$, $4-4-4-1$, $4-4-3-2$, $4-3-3-3$.

I tried to calculate the probabilities of the previous events. I demonstrate how I did it via an example.

Let's check the case when there are $10-2-1-0$ clovers in the packs. All deals have the same probabilities, so it is enough to check that case when the 1st player gets 10 clovers, the second player gets 2 clovers, the 3rd player gets 1 clover and the last palyer gets no clovers. Because all deals have the same probability there should be a $\frac{4!}{1!2!1!}$ factor in the following solution. In one deal there are $39!$ ways to share the non-clovers, and $13!$ ways to share the clovers. We can choose $10$ clovers out of $13$ cards $\binom{13}{10}$ ways in the case of the 1st player, $1$ clover out of $13$ clovers can be choosed $\binom{13}{1}$ ways in the case of the 2nd player, $\binom{13}{1}$ ways in the case of the 3rd player. All cases are $52!$, so the probability of that event when {there are $10$ clovers in one pack, $1$ clover in one pack, $1$ clover in another pack, $0$ clover in the last pack} is $$\frac{39!\cdot13!\cdot\binom{13}{10}\cdot\binom{13}{1}\cdot\binom{13}{1}}{52!}\cdot\frac{4!}{1!\cdot2!\cdot1!}.$$ Calculating all cases listed above we should get the proper distribution.

I would appreciate much easier solution for the problem, for example somehow calculating the $\mathbf{P}\left(X\leq i\right)$ distribution function, and in this case it would be easy to calculate with $$\mathbf{P}\left(X=i\right)=\mathbf{P}\left(X\leq i\right)-\mathbf{P}\left(X\leq i-1\right)=\mathbf{P}\left(X\leq i\right)-\left(\mathbf{P}\left(X=1\right)+...+\mathbf{P}\left(X=i-1\right)\right).$$

Or somehow calculating the probabilities with the complementer events.

Kapes Mate
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2 Answers2

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For $X=1$, the calculation is relatively simple, as there are only $4$ essentially different cases (there are four choices as to which players has all the clovers). For $X=2$, there are six choices as to which players have all the clovers. These two players have $26$ cards between them, and they each get $13$ cards, so we have $26C13$ ways of splitting cards between them. However, this doesn't actually get you $P(X=2)$, it gets you $P(X\leq2)$, so you have to subtract out the double-counted cases from $X=1$. And this double counting is more complicated than it may appear at first; when you find the probability that Player 1 and Player 2 are the ones with clovers, you've double counting both the case where Player 1 is the only one and the case where Player 2 is the only one. So the math on that can be tricky. With problems like these, it can be helpful to consider simpler problems (for instance, four clovers and four non-clovers distributed among four players, or four clovers and eight non-clovers) to see whether the formulas that you've come up with are giving results that make sense (with twelve cards, it's easy to come up with a computer program that gets the answer by brute force).

For $X=3$, there are four choices for who doesn't get any clovers, and there are $39C13$ choices for what non-clovers to give them. For $X=4$, if you calculate the previous three probabilities correctly, and you subtract the double-counted cases correctly, you can just do $P(X=4) = 1-P(X=3)-P(X=2)-P(X=1)$.

You also need to make sure that you're using the same denominator for each calculation. For instance, you can consider a hand to be different if the cards are dealt in a different order, or you can consider that the same hand, but you have to be consistent. So, for instance, when I said that there are $39C13$ choices for $X=3$, you may need to also multiply by the number of ways of distributing the remaining cards among the other three players, depending on how you're counting "different" configurations.

Acccumulation
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  • To be honest, it's not even trivial for me that there are only four cases when one player gets all the clovers. It is intuitive, since there are 4 players and only 1 player can have all the clovers. But consider that case when for example the 1st player gets all the clovers, the 2nd one gets all the hearts, the 3rd player gets all the pikes and the 4th palyer gets all the diamonds. (It is highly unlikely but it is just for the demonstration). This is one case. Consider the other case when still the 1st player gets all the clovers, but the 2nd gets all the pikes etc. This looks like another... – Kapes Mate Dec 24 '21 at 20:21
  • …outcome for me. Or we just make here only two categories: clovers and non-clovers? Are they the same cases in my example? – Kapes Mate Dec 24 '21 at 20:21
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    @KapesMate As I said, it depends on what you're using as the denominator. You could consider all 52! ordering of the cards, consider the first player to get the first 13, the second player to get the next 13, etc., and find how many configurations end up with $X=1$. You could consider a deal to be "essentially the same" if each player ends up with the same set of cards. But for $X=1$, you can consider just one player's hand, and take $4*39C13/52C13$. – Acccumulation Dec 24 '21 at 20:29
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This looks like a good place to apply the Generalized Principle of Inclusion and Exclusion. You can find a statement of the principle, references, and proofs on this site in Generalized inclusion-exclusion principle.

Let's say a deal of the deck has "Property $i$" if player $i$ has no clovers, for $1 \le i \le 4$, and let $S_j$ be the total of the probabilities of all the deals with $j$ of the properties, for $1 \le j \le 3$. Then $$\begin{align} S_1 &= \frac{\binom{4}{1} \binom{39}{13}}{\binom{52}{13}} \\ S_2 &= \frac{\binom{4}{2} \binom{39}{26}}{\binom{52}{26}} \\ S_3 &= \frac{\binom{4}{3} \binom{39}{39}}{\binom{52}{39}} \\ \end{align}$$ The probability that a deal has exactly $m$ of the properties is $X_m$. By the Generalized PIE, $$\begin{align} P(X=1) &= S_1 - \binom{2}{1} S_2 + \binom{3}{1} S_3 \\ P(X=2) &= S_2 - \binom{3}{2} S_3 \\ P(X=3) &= S_3 \end{align}$$

awkward
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  • I don't really understand why it is bad to calculate $\mathbf{P}\left(X=1\right)$ as $\frac{\binom{13}{13}\binom{39}{39}}{\binom{52}{13}}\binom{4}{3}$, $\mathbf{P}\left(X\leq2\right)=\frac{\binom{39}{26}\binom{13}{0}}{\binom{52}{26}}\binom{4}{2}$ and $\mathbf{P}\left(X=2\right)=\mathbf{P}\left(X\leq2\right)-\mathbf{P}\left(X=1\right)$. ... – Kapes Mate Dec 25 '21 at 18:50
  • ...We can calculate $\mathbf{P}\left(X\leq3\right)$ as $\frac{\binom{39}{13}\binom{13}{0}}{\binom{52}{13}}\binom{4}{1}$, so $\mathbf{P}\left(X=3\right)=\mathbf{P}\left(X\leq3\right)-\mathbf{P}\left(X\leq2\right)$. Something is not ok here. What is the problem? Anyway, do you have any idea how to calculate the probability of that event I gave in the other comment as a “last question”? – Kapes Mate Dec 25 '21 at 18:50
  • @KapesMate I'm sorry, but I don't follow your calculation of $P(X=1)$ at all. However, the difficulty with this problem, in general, is that it's easy to accidentally overcount. For example, one might think that $S_1$ in the solution above is $P(X=1)$, but it is not, because it includes some cases where $X=2$ or $X=3$. Hence the need for inclusion/exclusion. With regard to your "last question", I suggest you post it as a separate question. In general, it's not good to put a new question in a comment. – awkward Dec 26 '21 at 15:37
  • Note: I edited the solution on 26 Dec so that the notation in the final section of the solution agrees with that used in the OP. – awkward Dec 26 '21 at 15:41
  • ... I consider your suggestion to write an other question for the "last question", I just thought they belong to the same topic, and perhaps I could give a new solution to the original question if I could calculate the result of the "last question''. Anyway, thank you guys for your help. – Kapes Mate Dec 26 '21 at 20:36
  • But your edited solution doesn't intuitive...I can't belive $X=3$ has higher probability, than $X=1$. In the other way it would perfectly make sense, and I think it would be a good solution. If it would be backward (as I suggest), then your and my result are the same for $\mathbf{P}\left(X=1\right)$. But for $\mathbf{P}\left(X=2\right)$ I don't know why I can't calculate as $\mathbf{P}\left(X\leq2\right)-\mathbf{P}\left(X=1\right)$, where $\mathbf{P}\left(X\leq2\right)=\frac{\binom{39}{26}\binom{13}{0}}{\binom{52}{26}}\binom{4}{2}$??? – Kapes Mate Dec 26 '21 at 23:34
  • ..sorry...I wanted to write "$X=3$ has less probability, than..." – Kapes Mate Dec 27 '21 at 00:20
  • @KapesMate Just to be clear, $P(X=3)$ is much smaller than $P(X=1)$, which seems intuitive to me. – awkward Dec 27 '21 at 14:21
  • Ohh...I think we used different notations, and that could be the source of missunderstandings...Thank you for your help again... – Kapes Mate Dec 28 '21 at 17:39