This is a common mistake from not understanding the difference between probability mass functions, where the variable is discrete, and probability density functions, where the variable is continuous.  See [What is a probability distribution][1]:

> continuous probability functions are
> defined for an infinite number of
> points over a continuous interval, the
> probability at a single point is
> always zero. Probabilities are
> measured over intervals, not single
> points. That is, the area under the
> curve between two distinct points
> defines the probability for that
> interval. This means that the height
> of the probability function can in
> fact be greater than one. The property
> that the integral must equal one is
> equivalent to the property for
> discrete distributions that the sum of
> all the probabilities must equal one.all the probabilities must equal one.


  [1]: http://www.itl.nist.gov/div898/handbook/eda/section3/eda361.htm