A bag contains four balls. Two balls are drawn randomly and found them to be white. The probability that all the balls in the bag are white is
\(\frac{1}{2}\)
\(\frac{3}{5}\)
\(\frac{1}{4}\)
\(\frac{2}{3}\)
To find the probability that all 4 balls in a bag are white given that two balls drawn randomly are white, we proceed with:
1. Defining the Random Variable:
Let $X$ be the number of white balls in the bag. Since the bag contains 4 balls, $X$ can take values 0, 1, 2, 3, or 4.
Assuming each value is equally likely, so the probability is:
$ P(X=k) = \frac{1}{5} $
for $k = 0, 1, 2, 3, 4$.
2. Defining the Event:
Let $E$ be the event that two balls drawn randomly from the bag are both white.
We need to find $P(X=4 | E)$, the probability that all 4 balls are white given that the two drawn balls are white.
3. Applying Bayes' Theorem:
By Bayes' Theorem, we have:
$ P(X=4 | E) = \frac{P(E | X=4) P(X=4)}{P(E)} $
4. Calculating $P(X=4)$:
Since each value of $X$ is equally likely:
$ P(X=4) = \frac{1}{5} $
5. Calculating $P(E | X=4)$:
If $X=4$, all 4 balls in the bag are white. Therefore, if two balls are drawn, both must be white, so:
$ P(E | X=4) = 1 $
6. Calculating $P(E)$:
The total probability of drawing two white balls is given by summing over all possible values of $X$:
$ P(E) = \sum_{k=0}^4 P(E | X=k) P(X=k) $
The probability of drawing two white balls given $X=k$ is the number of ways to choose 2 white balls from $k$ white balls divided by the number of ways to choose 2 balls from 4 balls:
$ P(E | X=k) = \frac{\binom{k}{2}}{\binom{4}{2}} $
Since $\binom{k}{2} = 0$ for $k=0, 1$ (as we cannot choose 2 white balls if there are fewer than 2), the sum simplifies to:
$ P(E) = \sum_{k=2}^4 \frac{\binom{k}{2}}{\binom{4}{2}} P(X=k) $
Substituting $P(X=k) = \frac{1}{5}$ and $\binom{4}{2} = 6$, we get:
$ P(E) = \frac{1}{6} \cdot \frac{1}{5} \left[ \binom{2}{2} + \binom{3}{2} + \binom{4}{2} \right] $
Now compute the binomial coefficients:
$ \binom{2}{2} = 1, \quad \binom{3}{2} = 3, \quad \binom{4}{2} = 6 $
So:
$ P(E) = \frac{1}{6} \cdot \frac{1}{5} \cdot [1 + 3 + 6] = \frac{1}{6} \cdot \frac{1}{5} \cdot 10 = \frac{10}{30} = \frac{1}{3} $
7. Computing the Final Probability:
Now substitute into Bayes' Theorem:
$ P(X=4 | E) = \frac{P(E | X=4) P(X=4)}{P(E)} = \frac{1 \cdot \frac{1}{5}}{\frac{1}{3}} = \frac{1}{5} \cdot 3 = \frac{3}{5} $
Final Answer:
The probability that all 4 balls are white given that two drawn balls are white is $ \frac{3}{5} $.
Probability is defined as the extent to which an event is likely to happen. It is measured by the ratio of the favorable outcome to the total number of possible outcomes.
The set of possible results or outcomes in a trial is referred to as the sample space. For instance, when we flip a coin, the possible outcomes are heads or tails. On the other hand, when we roll a single die, the possible outcomes are 1, 2, 3, 4, 5, 6.
In a sample space, a sample point is one of the possible results. For instance, when using a deck of cards, as an outcome, a sample point would be the ace of spades or the queen of hearts.
When the results of a series of actions are always uncertain, this is referred to as a trial or an experiment. For Instance, choosing a card from a deck, tossing a coin, or rolling a die, the results are uncertain.
An event is a single outcome that happens as a result of a trial or experiment. For instance, getting a three on a die or an eight of clubs when selecting a card from a deck are happenings of certain events.
A possible outcome of a trial or experiment is referred to as a result of an outcome. For instance, tossing a coin could result in heads or tails. Here the possible outcomes are heads or tails. While the possible outcomes of dice thrown are 1, 2, 3, 4, 5, or 6.