The cumulative distribution function isThe total integral of the nonnegative probability density function is one.
For a random variable with a probability density function, a singleton has zero probability:Equivalently, its cumulative distribution function is continuous, so it has no jump at .
The integers form a countable set, and the events are disjoint. By countable additivity and part ii,Countability is essential: one cannot use the same sum argument over an arbitrary uncountable collection of zero-probability events.
Normalization of the probability density function requiresHence . The distribution is a Pareto distribution with minimum one and shape parameter .
For an integer , is the same event as . Integration for the Pareto distribution givesThe second identity subtracts two successive tail probabilities, equivalently integrating over . If includes zero, the extra case is and , since almost surely.
For a nonnegative integer-valued random variable , the tail-sum formula states . It follows by writing and using nonnegativity to interchange sum and expectation.
By part iii, is an integer with probability zero. Thus almost surely, andThe pointwise inequalities implyPutting and rearranging yieldsThis extracts bounds for an infinite series from simple rounding inequalities.
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