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While reading the motivation of complete measure space on Wikipedia, what I concluded was, completeness is not really necessary when we define on one measure space and it is necessary when we want to measure on product of measure spaces (is it true ?). If $\lambda$ is measure on $X$ and $Y$ then is it true that $\lambda^2$ is measure of $A$x$B$ and how ? I am not able to understand that $\lambda^2(A\times B)=\lambda(A)\times\lambda(B)$ ? Essentially what is the flaw in the measure without being complete ? Waiting for response. Thanks!

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One can define product measure spaces without completions. But Lebesgue measure is complete, and if we want two-dimensional Lebesgue measure, which is complete, to be be the product of one-dimensional Lebesgue measure with itself, we have to complete the product. – Michael Greinecker May 20 '12 at 14:06
By definition of Lebesgue measure we can see that it is complete , right, because subset of a set of measure zero has measure zero ie. the subset is measurable, right ?? But how would that change if we take a product ? – Theorem May 20 '12 at 14:20
If $N$ has measure zero, then $\lambda^2(N\times\mathbb{R})\lambda(N)\cdot\lambda(\mathbb{R})=0\cdot\infty=0$. So if $B$ is any subset of $\mathbb{R}$, then $\lambda^2(N\times B)$ would be $0$ if $\lambda^2$ were complete. But if $B$ is not measurable, the set $N\times B$ is not in the usual product $\sigma$-algebra. But it is in the completion. – Michael Greinecker May 20 '12 at 14:25
That a measure space is complete means that every subset of set with measure zero is measurable (and has therefore measure zero too). We know that $\lambda^2(N\times\mathbb{R})=0$ and $N\times B\subseteq N\times\mathbb{R}$ if $B\subseteq\mathbb{R}$. So if the product were complete, $N\times B$ would be in the product $\sigma$-algebra if it were complete. It is not, which is why we complete the product $\sigma$-algebra to get $\lambda^2(N\times B)=0$ for all $B\subseteq\mathbb{R}$. – Michael Greinecker May 20 '12 at 14:42
Btw: The Borel $\sigma$-algebra on $\mathbb{R}^2$ does equal the product $\sigma$ of the one-dimensional Borel $\sigma$-algebras! So the motivation Wikipedia gives might not be very convincing. – Michael Greinecker May 20 '12 at 14:47

We want measure spaces to be complete because we want to treat sets of measure zero as negligible. For example, if two functions $f$ and $g$ satisfy $f(x)=g(x)$ for all $x\in X\setminus N$, and $N$ has measure zero, then we'd like to treat $f$ and $g$ as essentially the same thing. However, without completeness it's possible that $f$ is measurable but $g$ is not.

The issue of completeness is brought into light by the product operation, because the product of complete measures is not always complete. For example, let $A\in [0,1]$ be a nonmeasurable set. The set $A\times \{0\}\subset [0,1]\times [0,1]$ is not measurable with respect to the product measure $\lambda\otimes\lambda$. However, $A\times \{0\}\subset [0,1]\times \{0\}$ and the latter set has product measure $0$. So, once we take the completion of the product measure, $A\times \{0\}$ becomes a measure $0$ set.

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Product measures are complete essentially by construction (they are almost always defined via the Carathéodory construction, which yields complete measure spaces). The point is that their restriction to the product $\sigma$-algebra (the algebra generated by the measurable rectangles) is usually not complete. – t.b. May 20 '12 at 15:17
@t.b. Well, Folland's "Real Analysis" is an exception to almost always, and since it was my textbook in measure theory... – user31373 May 20 '12 at 15:25
However, without completeness it's possible that f is measurable but g is not. What's wrong with this? Since $f$ and $g$ differ only on a null set, they can be regarded as the same in measure theory. – JHW Aug 21 '15 at 15:13
because the product of complete measures is not always complete. I don't see why this justifies the completion of a measure. If a product of complete measures is not complete, why do we need the completion of it? – JHW Aug 21 '15 at 15:21

One place in probability theory where complete measures are used is the theory of stochastic processes. We have a stochastic process $X_t$ indexed by reals $t$, so there are uncountably many of them. Certain combinations or these are important, but (as far as can be proved) only equal almost everywhere to a countable combination. With complete sigma-algebra, that is enough for us to conclude that this combination is measurable.

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I am giving an answer of this question Philosophically...

All intuition of Measure Theory comes from Probability Theory (finite measure theory ). In Probability certain event is impossible then all its sub events are also impossible (usually).

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In probability theory, it is very common to work with incomplete probability spaces. See for example here. – Michael Greinecker May 20 '12 at 14:45

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