We are given a binomial distribution with parameters \(n = 5\) (number of trials) and \(p = 0.6\) (probability of success). We need to find the probability \(P(X < 4)\).
The probability of obtaining exactly \(k\) successes in a binomial distribution is given by:
\[
P(X = k) = \binom{n}{k} p^k (1-p)^{n-k}
\]
where \(\binom{n}{k}\) is the binomial coefficient.
To find \(P(X < 4)\), we need to calculate the sum of probabilities for \(X = 0\), \(X = 1\), \(X = 2\), and \(X = 3\).
\[
P(X < 4) = P(X = 0) + P(X = 1) + P(X = 2) + P(X = 3)
\]
\[
P(X = 0) = \binom{5}{0} (0.6)^0 (0.4)^5 = 1 \times 1 \times 0.01024 = 0.01024
\]
\[
P(X = 1) = \binom{5}{1} (0.6)^1 (0.4)^4 = 5 \times 0.6 \times 0.0256 = 0.0768
\]
\[
P(X = 2) = \binom{5}{2} (0.6)^2 (0.4)^3 = 10 \times 0.36 \times 0.064 = 0.2304
\]
\[
P(X = 3) = \binom{5}{3} (0.6)^3 (0.4)^2 = 10 \times 0.216 \times 0.16 = 0.3456
\]
Add the probabilities calculated in the previous step:
\[
P(X < 4) = 0.01024 + 0.0768 + 0.2304 + 0.3456 = 0.6630
\]