The mean \( E(X) \) of a uniform distribution defined on the interval \([a, b]\) is given by the formula:
\[
E(X) = \frac{a + b}{2}
\]
For our case, where \( a = 0 \) and \( b = 9 \):
\[
E(X) = \frac{0 + 9}{2} = 4.5
\]
The variance \( \text{Var}(X) \) of a uniform distribution is calculated using the formula:
\[
\text{Var}(X) = \frac{(b - a)^2}{12}
\]
Substituting \( a = 0 \) and \( b = 9 \):
\[
\text{Var}(X) = \frac{(9 - 0)^2}{12} = \frac{81}{12} = 6.75
\]
The standard deviation \( \sigma(X) \) is the square root of the variance:
\[
\sigma(X) = \sqrt{\text{Var}(X)} = \sqrt{6.75} \approx 2.5981
\]
The cumulative distribution function \( F(x; a, b) \) for a uniform distribution is defined as:
\[
F(x; a, b) = \frac{x - a}{b - a}, \quad a \leq x \leq b
\]
To find the probability \( P(0 \leq X \leq 9) \):
\[
P(0 \leq X \leq 9) = F(9) - F(0) = 1.0 - 0.0 = 1.0
\]
Since the probability of each digit being selected is equal, the lottery digits have a uniform distribution, not a normal distribution. Therefore, the correct answer to the question is:
\(\boxed{A}\)