(i) The two conditions for a binomial distribution are:

1. There are a fixed number of trials.
2. Each trial is independent.
3. There are only two possible outcomes for each trial.
4. The probability of success is constant for each trial.

(ii) Let the random variable \(X\) represent the number of cars made by Ford. \(X\) follows a binomial distribution with parameters \(n = 14\) and \(p = 0.28\).

We need to find \(P(X < 4)\), which is the sum of probabilities \(P(X = 0) + P(X = 1) + P(X = 2) + P(X = 3)\).

Using the binomial probability formula:

\(P(X = k) = \binom{n}{k} p^k (1-p)^{n-k}\)

Calculate each probability:

\(P(X = 0) = \binom{14}{0} (0.28)^0 (0.72)^{14} = 0.72^{14} = 0.0101\)

\(P(X = 1) = \binom{14}{1} (0.28)^1 (0.72)^{13} = 14 \times 0.28 \times 0.72^{13} = 0.0548\)

\(P(X = 2) = \binom{14}{2} (0.28)^2 (0.72)^{12} = 91 \times 0.28^2 \times 0.72^{12} = 0.1385\)

\(P(X = 3) = \binom{14}{3} (0.28)^3 (0.72)^{11} = 364 \times 0.28^3 \times 0.72^{11} = 0.2154\)

Summing these probabilities gives:

\(P(X < 4) = 0.0101 + 0.0548 + 0.1385 + 0.2154 = 0.419\)