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Let $I = [0,1]$. Suppose we define $A$ as the space of all functions $f:I\to \mathbb{R}$ which are Riemann integrable. We can put a norm on this space $A$, by defining $||f|| = \int_I |f|$. Of course, this is not quite a norm, and we identify $f\sim g$ iff $\int_I |f-g| = 0$. The space $B = (A/\sim)$ will then we a normed function space.

Unfortunately, $B$ is not complete. However, we can complete it, and let us call the new resulting space $C$ (this is a Banach space). In classical real analysis we typically call this $L^1([0,1])$. However, we completely bypassed the construction of the Lebesgue integral.

We can then say $E\subseteq [0,1]$ is a "measurable" set if and only if $\chi_E\in C$ (the indictator function). We also define the Lebesgue measure of $E$ to be the quantity $||\chi_E||$, where $||\cdot ||$ is the extended norm to the Banach space $C$.

I never seen books take this approach to real analysis. This non-standard approach seems to be a lot simpler. Perhaps, there are some issues with this?

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    This is indeed fine. However, where do you go from here? What's really useful is abstract measure theory, not just doing integration over $\mathbb R$ – Andrew Nov 30 '23 at 19:46
  • Then $S:=\mathbb Q\cap[0,1]$ would not be measurable, since $\chi_S\not\in C$. – Vercassivelaunos Nov 30 '23 at 19:53
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    @Vercassivelaunos You mean $\chi_S\not \in B$. However, $\chi_S\in C$. – Nicolas Bourbaki Nov 30 '23 at 21:01
  • @Andrew In a probability space you can define integration/expectation in a similar way. Once you have a measure/probability function you can essentially recreate "Riemann" integration by using functions whose range is a finite set of numbers. Using the same approach as before we can enlarge expectation to more general random variables. – Nicolas Bourbaki Nov 30 '23 at 21:06
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    “By using functions whose range is a finite set of numbers.” It would be nice to elaborate on this, and how this is not simply the traditional approach to Lebesgue integration. Riemann integration refers to approximating the integral by partitioning the domain. On an abstract space, how exactly are you portioning the domain? Even concretely, how do you partition $C[0,\infty)$ equipped with the topology of uniform convergence, or partition the space of probability measures with finite first moment? – Andrew Nov 30 '23 at 21:50
  • topology of uniform convergence on compacts* – Andrew Nov 30 '23 at 22:02
  • I never seen books take this approach to real analysis. --- See Section 7.2 (pp. 301-305) in Analysis in Euclidean Space by Kenneth Hoffman (1975; 2007 Dover reprint). A similar approach can be used starting with step functions, continuous functions, piecewise linear functions, polynomials -- see Ch. 5 & Exs. 8, 9 on p. 165 of An Introduction to Analysis and Integration Theory by Esther R. Phillips (1971; 1984 Dover reprint). – Dave L. Renfro Nov 30 '23 at 22:15
  • A functional analytic approach is used to define the integral of Banach space valued functions. However, the advantage of the direct construction for real valued integrands is that you can handle functions that take the value $\infty$ and the theorems all work for this case. – Mason Dec 01 '23 at 00:30
  • What you described is in essence what Danielle did in 1918-1919. – Mittens Dec 01 '23 at 01:24
  • @Andrew You can partition $[0,\infty)$ by simply using partitions of unity and reducing everything back down to compact intervals. This is essentially how integration is defined in a smooth manifold. – Nicolas Bourbaki Dec 01 '23 at 03:53
  • @Mittens So why is it that Universities do not teach this approach? It is so much more elegant and gets to the point faster. The now-standard approach to analysis is overly repetitive. You reprove the same theorem over and over, and it is too long to get to anything interesting. – Nicolas Bourbaki Dec 01 '23 at 04:00
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    @NicolasBourbaki: Some places do cover Daniell's approach to Integration. There are also books that cover that approach (Bichteller, K. Integration: A functional approach, Birkhauser, 1998; Simon, B. Analysis Vol 1 (real Analysis), AMS amongst others). As to why most courses build integration from measure theory, I don't know. There is some discussion about the here at MSE. – Mittens Dec 01 '23 at 04:52
  • @NicolasBourbaki Imho: In teaching at universities terseness and elegance is not always the best approach. Students have started with Riemann sums and it is not a bad idea to introduce the Lebesgue integral starting with $\sigma$-algebras, measures and simple (step) functions. Nonetheless: Here I introduce you to another enthusiastic aficionado of a different approach. – Kurt G. Dec 01 '23 at 08:04
  • @NicolasBourbaki: Starting from Riemann integral, you can look at Shilov's book on integration which takes it to the Lebesgue integral using linear methods similar to Daniell's. All the main ideas are explained there. That book is a cheap Dover book and is worth having it in your personal library. – Mittens Dec 01 '23 at 17:45

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