Step 1: Understanding the Concept:
The Poisson distribution is a discrete probability distribution that models the number of events occurring in a fixed interval of time or space.
Key Formula or Approach:
The probability mass function of a Poisson distribution with parameter (mean) $\lambda$ is:
\[ P(X = x) = \frac{e^{-\lambda} \lambda^x}{x!}, \quad x = 0, 1, 2, \dots \]
Step 2: Detailed Explanation:
Given that the mean of the distribution is:
\[ \lambda = e \]
Substitute $\lambda = e$ into the Poisson probability mass function:
\[ P(X = x) = \frac{e^{-e} e^x}{x!} \]
Combine the exponential terms in the numerator using exponents laws ($e^a \cdot e^b = e^{a+b}$):
\[ P(X = x) = \frac{e^{x-e}}{x!} \]
Rewriting this in functional notation:
\[ P(X = x) = \frac{\exp(x-e)}{x!} \]
Step 3: Final Answer:
The derived probability mass function is $\exp(x-e)/x!$, which matches Option (A).