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Question

If a fair die is rolled 4 times, then what is the probability that there are exactly 2 sixes?

This question was previously asked in
NDA II 2019 GAT Previous Year Paper (17-Nov-2019)
The correct answer is \(\frac{{25}}{{216}}\)

Probability of Exactly 2 Sixes in 4 Fair Die Rolls

This problem involves calculating the probability of a specific outcome (getting a six) occurring a fixed number of times (exactly 2) in a fixed number of independent trials (4 rolls of a fair die). This is a classic example of a binomial probability distribution problem.

Understanding Binomial Probability

A binomial probability distribution applies when there are:

  • A fixed number of trials (n). Here, n = 4 (4 rolls).
  • Each trial has only two possible outcomes: "success" or "failure". Here, "success" is rolling a six, and "failure" is not rolling a six.
  • The probability of success (p) is constant for each trial. For a fair die, the probability of rolling a six is \(p = \frac{1}{6}\).
  • The trials are independent. The outcome of one roll does not affect the outcome of others.

The probability of failure (q) is \(q = 1 - p = 1 - \frac{1}{6} = \frac{5}{6}\).

We want to find the probability of getting exactly \(k\) successes in \(n\) trials. The formula for binomial probability is:

\(P(X=k) = \binom{n}{k} p^k q^{n-k}\)

where \(\binom{n}{k}\) is the binomial coefficient, calculated as \(\binom{n}{k} = \frac{n!}{k!(n-k)!}\).

Calculating the Probability

In this problem, we have:

  • Number of trials, \(n = 4\)
  • Number of successes (exactly 2 sixes), \(k = 2\)
  • Probability of success (rolling a six), \(p = \frac{1}{6}\)
  • Probability of failure (not rolling a six), \(q = \frac{5}{6}\)

We need to calculate \(P(X=2)\).

First, calculate the binomial coefficient \(\binom{4}{2}\):

\(\binom{4}{2} = \frac{4!}{2!(4-2)!} = \frac{4!}{2!2!} = \frac{4 \times 3 \times 2 \times 1}{(2 \times 1)(2 \times 1)} = \frac{24}{4} = 6\)

Next, calculate the probabilities raised to their respective powers:

  • \(p^k = \left(\frac{1}{6}\right)^2 = \frac{1^2}{6^2} = \frac{1}{36}\)
  • \(q^{n-k} = \left(\frac{5}{6}\right)^{4-2} = \left(\frac{5}{6}\right)^2 = \frac{5^2}{6^2} = \frac{25}{36}\)

Now, multiply these values according to the binomial probability formula:

\(P(X=2) = \binom{4}{2} p^2 q^2 = 6 \times \left(\frac{1}{36}\right) \times \left(\frac{25}{36}\right)\)

Multiply the fractions:

\(P(X=2) = 6 \times \frac{1 \times 25}{36 \times 36} = 6 \times \frac{25}{1296}\)

Now, multiply 6 by the fraction:

\(P(X=2) = \frac{6 \times 25}{1296} = \frac{150}{1296}\)

Simplify the fraction by dividing both the numerator and the denominator by their greatest common divisor. Both are divisible by 6:

\(\frac{150 \div 6}{1296 \div 6} = \frac{25}{216}\)

So, the probability of getting exactly 2 sixes when a fair die is rolled 4 times is \(\frac{25}{216}\).

Summary of Calculation Steps

  1. Identify \(n=4\), \(k=2\), \(p=1/6\), \(q=5/6\).
  2. Calculate the binomial coefficient \(\binom{4}{2} = 6\).
  3. Calculate \(p^k = (1/6)^2 = 1/36\).
  4. Calculate \(q^{n-k} = (5/6)^2 = 25/36\).
  5. Multiply the results: \(6 \times \frac{1}{36} \times \frac{25}{36}\).
  6. Simplify the product: \(\frac{150}{1296} = \frac{25}{216}\).

The final probability is \(\frac{25}{216}\).

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Important Questions from Binomial Distribution

  1. In a Binomial distribution, the mean is three times its variance. What is the probability of exactly 3 successes out of 5 trials?

  2. If mean and variance of a Binomial variate X are 2 and 1 respectively, then the probability that X takes a value greater than 1 is

  3. For Binomial distribution, n = 10 and p = 0.6, E(X 2) (second moment about origin) is:

  4. Indicate the correct answer for the combination from the following regarding the conditions for the applicability of a binominal distribution:

    (a) There are n independent trials

    (b) Each trial has only two possible outcomes

    (c) The probabilities of two outcomes do not remain constant

    (d) The trials are independent

    Which of the following options is correct?

  5. Find out the fallacy if any in the statement:

    “The mean and the variance of a binomial distribution is 16.2 and 29.4 respectively.”

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