Balls are randomly taken out of a box of 4 red and 6 green balls, without replacement, until we have a ball of each colour.

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What is the probability of

  1. Needing exactly two draws
  2. Needing two or three draws
  3. Needing to make exactly three draws if the first two balls drawn are of the same colour

For part 1. I computed that the number of ways we can choose a red followed by a green or vice versa is $|A|=6\cdot4$. The sample space itself has $10\choose2$ items so $$P(A)=\frac{6\cdot4}{10\choose2}=\frac{8}{15}$$ Part 2. and 3. posed the same issue for me. I approached part 2. with two events $A$: It takes two throws, $B$: It takes three throws. Then those two events are mutually exclusive so $P(A\cup B)=P(A)+P(B)$ which we are looking for. Here is the issue for 2. and 3.. I don't know how to calculate the probability that the first two are of the same colour. I thought that it may be $$\frac{{6\choose4}+{4\choose2}}{10\choose2}$$ But even if this were right I don't know how to mathematically express the fact that the 3rd one must be different. My theory is that (assuming the above is correct) it may be $$\frac{{6\choose4}\cdot{4\choose1}+{4\choose2}\cdot{6\choose 1}}{10\choose3}$$

EDIT 1

I got solutions for part 1. and 3. but am still wrapping my head around 2. For 1. you have the event $A$: The balls are of different colours. For $A$ we have $|A|=6\cdot4+4\cdot6$ and a sample space $|\Omega|=10\cdot9$ hence $P(A)=\frac{8}{15}$ similar to the above. For 3. we need to find $P(B|C)$. We know that $$P(B|C)=\frac{P(B\cap C)}{P(C)}$$. Furthermore $P(B\cap C)=P(B)$ because $B\cap C$ is the event that three balls are chosen. If three balls are chosen then the first two must have been the same colour. Hence $$P(B|C)=\frac{P(B)}{P(C)}=\frac47$$

EDIT 2 Question 2. has been resolved as well. Given that all of the events involved are pairwise disjoint the answer is just the sum of the prob that two are drawn and three are drawn. $$P(A)+P(B)=\frac{12}{15}$$

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To need exactly $n$ draws is the event for obtaining $n-1$ consecutive draws of one colour followed by one ball of the other.

$$\dfrac{\dbinom 4{n-1}\dbinom 61+\dbinom 6{n-1}\dbinom 41}{\dbinom{10}{n-1}\dbinom {9-n}1}\tag{$n\in\{2,3,4,5,6,7\}$}$$

Note: There is importance in distinguishing the earlier draws from the possible terminal draw.


The probability for needing exactly two draws to obtain different colored balls, when drawing without replacement from four red and six green balls is: the probability for obtaining one balls of one colour then one ball of the other, when drawing a ball then another.

$$\dfrac{\dbinom 41\dbinom 61+\dbinom 61\dbinom 41}{\dbinom{10}1\dbinom 91}=\dfrac{4\cdot 6+6\cdot 4}{10\cdot 9}$$

Which is coincidentally equal to $\binom 41\binom 61/\binom{10}2$.

Likewise:

The probability for needing exactly three draws to obtain different colored balls, when drawing without replacement from four red and six green balls is: the probability for obtaining two balls of one colour then one ball of the other, when drawing two balls then a third.

$$\dfrac{\dbinom 42\dbinom 61+\dbinom 62\dbinom 41}{\dbinom{10}2\dbinom{8}1}=\dfrac{4\cdot 3\cdot 6+6\cdot 5\cdot 4}{10\cdot 9\cdot 8}$$

But even if this were right I don't know how to mathematically express the fact that the 3rd one must be different.

That was how. The denominator may be any of the following:

$$\binom{10}3\binom 31=\binom{10}2\binom 81=\binom {10}1\binom 92$$

  • Select 3 from 10 balls, and 1 of those 3 (to be the last).
  • Select 2 from 10 balls, then 1 from the remaining 8.
  • Select 1 from 10 balls (to be the third), then 2 from the remaining 9 (to be before it).

So the probability for needing two or three draws is: ...



The probability that exactly three draws are needed when given that the first two draws are of the same colour has the form:

$$\dfrac{\mathsf P(R_1,R_2,G_3)+\mathsf P(G_1,G_2,R_3)}{\mathsf P(R_1,R_2)+\mathsf P(G_1,G_2)}=\dfrac{\lvert R_1,R_2,G_3\rvert+\lvert G_1,G_2,R_3\rvert}{\lvert R_1,R_2,(R_3\cup G_3)\rvert+\lvert G_1,G_2,(R_3\cup G_3)\rvert}$$

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Alternative approach:

First see my comments, following the original question. This response is an extension of those comments. Normally, probability problems such as this are best attacked with Combinatorics, which is represented by Graham Kemp's answer.

However, the order that the questions (1,2,and 3) are posed is suspicious. The problem composer may have intended that the problem solver try to see the relationships among the questions, and use that to guide not only the order that the questions are attacked, but whether Combinatorics might reasonably be bypassed.

The analysis below, will exclusively stay with a probability of events approach, rather than Combinatorics. Also, the analysis below will give the details indicated in my comments.


Balls are randomly taken out of a box of 4 red and 6 green balls, without replacement, until we have a ball of each colour.

What is the probability of

  1. Needing exactly two draws
  2. Needing two or three draws
  3. Needing to make exactly three draws if the first two balls drawn are of the same colour

I will attack question 1 first. Then question 3. Then question 2.

$\underline{\text{Question 1}}$
The only way of needing exactly two draws is if the 1st and 2nd draw are not the same color. Letting $R$ denote the event of selecting a red ball, and $G$ denote the event of selecting a green ball, the probability of $RG$ occuring + probability of $GR$ occurring is

$$\left[\frac{4}{10} \times \frac{6}{9}\right] + \left[\frac{6}{10} \times \frac{4}{9}\right] = \frac{48}{90} = \frac{8}{15}. \tag1 $$

In the first LHS term, after the red ball is selected, there are $9$ balls left, $6$ of which are green. So (1) above represents conditional probabilities. That is, after the red ball was selected, the probability that the 2nd draw would be green had changed from $\displaystyle ~\frac{6}{10}~$ to $\displaystyle ~\frac{6}{9}$.


$\underline{\text{Question 3}}$
I advise attacking this question next, since it will be used to answer Question 2.

Let $E_x$ denote the event that the first two draws were the same color. Let $E_y$ denote the event that the third draw is of a different color from the 1st $2$ draws (i.e. that the 3rd draw is the other color). Then Question 3 is specifically asking for $p(E_y|E_x)$.

This means that you are being asked about two mutually exclusive events:

  • 3rd draw green, assuming 1st two draws red.
    Probability is $~\displaystyle \frac{6}{8}$, since at this point, it is assumed that there are $8$ balls left, $6$ of which are green.
  • 3rd draw red, assuming 1st two draws green.
    Probability is $~\displaystyle \frac{4}{8}.$

However, here you have a problem. Although you can compute $p(E_y|E_{RR})$ and $p(E_y|E_{GG})$ the problem requires (in effect) a weighted average. So, Bayes Theorem must be employed.

Using the syntax of $(R,S)$ to denote that events $R$ and $S$ both occur, formally, you must compute :

$$\frac{p\left(E_y,E_{RR}\right) + p\left(E_y,E_{GG}\right)}{p\left(E_{RR}\right) + p\left(E_{GG}\right)}. \tag2 $$

Letting $E_{3R}$ and $E_{3G}$ denote the events of 3rd draw red and 3rd draw green, respectively, (2) above equals

$$\frac{p\left(E_{3G},E_{RR}\right) + p\left(E_{3R},E_{GG}\right)}{p\left(E_{RR}\right) + p\left(E_{GG}\right)}. \tag3 $$

In (3) above, the numerator is

$$\left[\frac{4}{10} \times \frac{3}{9} \times \frac{6}{8}\right] + \left[\frac{6}{10} \times \frac{5}{9} \times \frac{4}{8}\right] = \frac{72 + 120}{720} = \frac{4}{15}.$$

In (3) above, the denominator does not need to be computed. This is because the denominator, the probability of the first two draws being the same color, may be inferred from Question 1. That is, Question 1 asked for the probability of the complementary event, and was computed to be $~\displaystyle \frac{8}{15}.$

Therefore, in (2) above, you immediately know that the denominator equals $~\displaystyle 1 - \frac{8}{15} = \frac{7}{15}.$

Therefore (3) above evaluates to

$$\frac{\frac{4}{15}}{\frac{7}{15}} = \frac{4}{7}. \tag4$$


$\underline{\text{Question 2}}$
This question is attacked last, because virtually no further Math computations are required here. This question is asking for the combined probability of two mutually exclusive events:

  • Exactly $2$ draws needed.
    From Question 1, probability equals $~\displaystyle \frac{8}{15}.$

  • Exactly $3$ draws needed.
    This probability may be inferred, using the computations/analysis already done in Questions 1 and 3.

Let $E_1$ denote the event that the first two draws are the same color. Let $E_2$ denote the event that the 3rd draw is a different color from the first $2$ draws.

Then, the probability of exactly $3$ draws being needed equals

$$p(E_1) \times p(E_2 | E_1).$$

As discussed in Question 3, $~\displaystyle p(E_1) = 1 - \frac{8}{15} = \frac{7}{15}.$

As answered directly, in Question 3, $~\displaystyle p(E_2 | E_1) = \frac{4}{7}.$

Therefore, $~\displaystyle p(E_1) \times p(E_2 | E_1) = \frac{7}{15} \times \frac{4}{7} = \frac{4}{15}.$

Therefore, the overall answer to question 2 is

$$\frac{8}{15} + \frac{4}{15} = \frac{12}{15} = \frac{4}{5}.$$


I do not normally recommend a probability of events approach to a problem of this sort. Normally, a Combinatorics approach is best. However, in my opinion, Probability Theory requires that the student's intuition be stretched. In this unusual situation, because of the interplay between the questions, the probability of events approach is better suited to stretching the student's intuition.


Edit
Although I do not recommend that the following approach be used to (indirectly) answer Question 2, this approach will expand the student's intuition. Since the answer to Question 2 is $~\displaystyle \frac{4}{5}~$, you can infer that the probability of the complementary event, needing more than $3$ draws, is $~\displaystyle \frac{1}{5}.~$

This implies that there is an alternate method of computing the answer to Question 2. You could compute $1 - p(\text{needing more than 3 draws}).$

The probability of needing more than $3$ draws can be computed using Questions 1 and $3$ as follows:

First, you calculate the probability that $2$ draws are insufficient. This is $~\frac{7}{15}.~$

Then, you calculate (in effect) the probability that $3$ draws are insufficient, given that $2$ draws were insufficient.

Question 3 had you compute the complementary probability, which was $~\displaystyle \frac{4}{7}$.

Therefore, the probability that $3$ draws are insufficient, given that $2$ draws are insufficient is $~\displaystyle \frac{3}{7}.$

Therefore, the overall probability of needing more than $3$ draws is $~\displaystyle \frac{7}{15} \times \frac{3}{7} = \frac{3}{15} = \frac{1}{5}.$

Therefore, Question 2 may be answered by reasoning that the probability of needing at most $3$ draws is $~\displaystyle 1 - \frac{1}{5} = \frac{4}{5}.$