We already saw how a standard deck of cards forms a nice setting for studying both Coupon Collector problem without replacement and Birthday problem without replacement. Here we extend those to some more problems for a fun!
The first problem is to ask for the expected number of cards such that we have atleast one matching suit or one matching rank. This problem is relatively easy. We proceed using the same idea as before.
Let $X$ be the random variable denoting the number of cards need to get atleast one matching suit or rank. Then, the probability that we need more than $k$ cards to get this,
$\displaystyle \mathbb{P}(X>k)=\frac{k!\binom{13}{k}\binom{4}{k}}{\binom{52}{k}}$
That is, we are finding the probability that we neither have a mathcing suit nor a matching rank after we have drawn $k$ cards without replacement. Therefore,
$\displaystyle \mathbb{E}(X)=\sum_{k>0}\mathbb{P}(X>k)$
So, we need, on average, $\approx 3.0799$ cards to get either a matching suit or a matching rank when drawing cards without replacement from a randomly shuffled standard deck of cards.
To simplify text, let $S_k$ denote the event of having atleast one matching suit after having drawn $k$ cards without replacement and $R_k$ denote the same event for rank. Then, we know $\mathbb{P}(S^c_k)$, $\mathbb{P}(R^c_k)$, and $\mathbb{P}(S^c_k\text{ and }R^c_k)$.
Using Inclusion-Exclusion principle, we have
$\displaystyle \mathbb{P}(S^c_k \text{ or } R^c_k)=\mathbb{P}(S^c_k)+\mathbb{P}(R^c_k)-\mathbb{P}(S^c_k\text{ and }R^c_k)$
This allows to calculate the expected number of cards need to get both a matching suit and a matching rank when drawing cards without replacement. If $X$ denotes this random variable, then
$\mathbb{P}(X>k)=1-\mathbb{P}(S_k\text{ and }R_k)=\mathbb{P}(S^c_k \text{ or } R^c_k)$
This shows that
$\displaystyle \mathbb{E}(S \text{ and } R)=\mathbb{E}(S)+\mathbb{E}(R)-\mathbb{E}(S\text{ or }R)\approx 3.2678 + 5.6965 - 3.0799=5.8844$
Therefore, we need, on average, $\approx 5.8844$ cards to get both a matching suit and a matching rank when drawing cards without replacement from a randomly shuffled standard deck of cards.
Now we ask a similar question in the Coupon collector problem. That is, we seek the expected number of cards needed to collect all suits and all ranks when drawing cards without replacement from a well shuffled pack of cards.
Like we did before, we will be using idea of negative Geometric random variable and the Min-Max identity. Let $X_k$ ($k \in \{\text{Spades}, \text{Clubs}, \text{Hearts}, \text{Diamonds}\}$)be the random number of draws needed without replacement to get first suit. Similarly, let $Y_k$ for $1\leq k \leq 13$ be the corresponding random variables for ranks.
If we let $Z$ denote the random number of draws needed to collect all suits and ranks, and $A$ be the set $\{X_S, X_C,\cdots,Y_1,Y_2,\cdots,Y_{13}\}$, then by the Min-Max identity, we know
$\displaystyle \mathbb{E}(Z)=\mathbb{E}(\text{max }A)=\sum_{M \subset_\emptyset A}(-1)^{|M|}\mathbb{E}(\text{min }M)$
where we have used $\subset_\emptyset$ to denote a non-empty subset.
It just remains to calculate the expected values of the subsets. This is not very difficult and we can proceed as we did in the earlier post. For example, let's solve for $M=\{X_S,X_C,Y_5,Y_6,Y_7\}$.
Then $\mathbb{E}(\text{min }M)$ is the expected number of cards needed to get either a Spade or a Clubs or any of ranks $5$, $6$ or $7$. This is again a Negative Geometric variable with population size $N=52$ and "successes" $K=13+13+4+4+4-6=32$. We are subtracting the six cards which are the 5, 6 and 7 of Clubs and Spades to avoid double counting.
Now using the expectation of Negative Geometric variable, we easily see that $\mathbb{E}(\text{min }M)=(52+1)/(32+1)$.
Expanding the idea, the expected value of $Z$ can be seen to be
$\begin{align}\displaystyle \mathbb{E}(Z)&=(52+1)\left[1-\sum_{i=0}^4\sum_{j=0}^{13}\binom{4}{i}\binom{13}{j}\frac{(-1)^{i+j}}{13i+4j-ij+1}\right]\\ &=(52+1)\left[1-(-1)^{4+13}\sum_{i=0}^4\sum_{j=0}^{13}\binom{4}{i}\binom{13}{j}\frac{(-1)^{i+j}}{52-ij+1}\right]\end{align}$
Evaluating this with Wolfram Alpha, we finally see that the number of cards needed, on average, to collect atleast one card from each suit and rank when drawing cards without replacement from a shuffled deck of cards is $\approx 27.9998$, very close to an integer.
Yours Aye
Me