Conditional Probability and Drawing Cards

In summary, to win three cards of a suit, E or W must choose 3 from the three left, then choose 10 more from the 23 cards.
  • #1
Sizwe
2
0

Homework Statement



A standard deck of 52 cards of 4 suits, each with 13 denominations, is well shuffled and dealt out to four players, N, S, E and W, who each receive 13 cards. If N and S have exactly ten cards of a specified suit between them, show that the probability that three remaining cards of the suit are in one player's hand (either E or W) is 0.22

Homework Equations



[itex]P(A | B) = \frac{P(A \cap B)}{P(B)}[/itex]

The Attempt at a Solution



I completed this question a few months ago with the solution:

[itex]\frac{2\binom{23}{10}}{\binom{26}{13}\binom{13}{13}} = 0.22[/itex]

Problem is, I have no idea how I got to that solution. I try now but end up with probabilities greater than 1, or very very small probabilities. Some clarification on how I got my solution, or how anyone would solve this, would be appreciated :)
 
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  • #2
Sizwe said:

Homework Statement



A standard deck of 52 cards of 4 suits, each with 13 denominations, is well shuffled and dealt out to four players, N, S, E and W, who each receive 13 cards. If N and S have exactly ten cards of a specified suit between them, show that the probability that three remaining cards of the suit are in one player's hand (either E or W) is 0.22

Homework Equations



[itex]P(A | B) = \frac{P(A \cap B)}{P(B)}[/itex]

The Attempt at a Solution



I completed this question a few months ago with the solution:

[itex]\frac{2\binom{23}{10}}{\binom{26}{13}\binom{13}{13}} = 0.22[/itex]

Problem is, I have no idea how I got to that solution. I try now but end up with probabilities greater than 1, or very very small probabilities. Some clarification on how I got my solution, or how anyone would solve this, would be appreciated :)

Once N and S have their cards, there are 26 cards left for E and W, 3 of which are of the particular suit. For E to get all three, he must choose 3 from those 3 then 10 more from the remaining 23. Does that help?
 
  • #3
LCKurtz said:
Once N and S have their cards, there are 26 cards left for E and W, 3 of which are of the particular suit. For E to get all three, he must choose 3 from those 3 then 10 more from the remaining 23. Does that help?

Your formula is weird. It looks wrong, but happens by accident to deliver a correct result---essentially because some of the factors or divisors are 1.0, and so do not affect anything. I suggest you try to use a formula similar to yours on the problem of computing the probability that E gets 2 of the "special" cards (instead of 3). Then you really will see a difference between your formula and the correct one.

RGV
 
  • #4
LCKurtz said:
Once N and S have their cards, there are 26 cards left for E and W, 3 of which are of the particular suit. For E to get all three, he must choose 3 from those 3 then 10 more from the remaining 23. Does that help?

Yes :) Thank you! I see it now as give N and S their cards including ten from the suit. Then give the three remaining to either E or W (hence I mutliply by 2), then all that remains is for E or W to choose 10 cards from the 23 left over. Any other choices made cancel through division of the number of ways N and S can get 10 of a suit between them (the denominator). I think the lesson learned here is to show all my steps :P

Thanks again guys :)
 

FAQ: Conditional Probability and Drawing Cards

1. What is conditional probability?

Conditional probability is the likelihood of an event occurring given that another event has already occurred. It takes into account the relationship between two events and is calculated by dividing the probability of both events occurring by the probability of the first event occurring.

2. How is conditional probability used in drawing cards?

In drawing cards, conditional probability is used to determine the likelihood of drawing a certain card from a deck, given that another card has already been drawn. This can be helpful in games of chance such as poker or blackjack, where knowing the probability of certain cards being drawn can give players an advantage.

3. Can conditional probability change based on previous outcomes?

Yes, conditional probability can change based on previous outcomes. This is because the probability of an event occurring can be affected by the occurrence of another event. For example, the probability of drawing a red card from a deck decreases if a red card has already been drawn.

4. How is conditional probability different from regular probability?

Regular probability looks at the likelihood of an event occurring without taking into account any other events. Conditional probability, on the other hand, takes into account the relationship between two events and adjusts the probability accordingly.

5. What is the formula for calculating conditional probability?

The formula for calculating conditional probability is P(A|B) = P(A and B) / P(B), where P(A|B) represents the probability of event A occurring given that event B has already occurred, P(A and B) represents the probability of both events occurring, and P(B) represents the probability of event B occurring.

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