Are the two formulas for total variation distance equivalent?

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boboYO
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I was doing some reading and I came across this:

http://en.wikipedia.org/wiki/Total_variation_distance_of_probability_measures

So apparently for the finite case,

[tex]\max_{x} ( \left| P(x) - Q(x) \right|)\quad \mbox{ is equivalent to}\quad \frac{1}{2} \sum_x {\left| P(x)-Q(x)\right|}[/tex]


but isn't this is a counterexample?
Code:
x         1        2        3        4
P(x)    0.25     0.25     0.25      0.25

Q(x)    0.10     0.20     0.35      0.35

|P-Q|   0.15     0.05     0.10      0.10

sum(|P-Q|)/2= 0.2

max(|P-Q|)=0.15



So I was thinking, maybe they meant 'equivalent' in a different sense? Could somebody please explain?
 
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I believe they might mean that those two metrics define the same topology on the set of probability measures.
 
Rochfor1 is correct. "Equivalent" simply means that they will give the same results in any probability measures, not that they are equal.