TITLE: Poisson and Binomial Distribution
QUESTION [0 upvotes]: I need help with a simple question.

Suppose that a hairdresser with a single store has 5 customers arrive
  on average every hour while they are open. Assume that customers’
  arrivals don’t depend on time of day or on whether other customers
  have arrived. We wish to model the arrival of customers in the morning
  (9am to 12 midday). Suppose we define the random variable X as the
  number of customers arriving in the morning. What would be a suitable
  distribution for X, along with its mean and variance?
a) Poisson, lambda = 15; mean = 15; variance = 15;
b) Poisson, lambda = 15; mean = 15; variance = 225
c) Binomial, n = 15, p = 0.5; mean = 15; variance = 15  
d) Binomial, n = 15, p = 0.5; mean = 15; variance = 225


I know that poisson is used with discreet events. And binomial with continuous events. In this case I would choose a because the mean is equal to the variance. 
Did I choose correctly? or is the case in this question is a special case?

REPLY [0 votes]: Let $\{N(t):t\geqslant0\}$ be a Poisson process with rate $\lambda=5$. Then $Y=N(3)$ which has Poisson distribution with mean $3\cdot5=15$. Since the variance of a Poisson distribution is equal to its mean, the correct choice is a).
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