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[[Jets7.1 _OldKiwi| Solution to 7.1]]
 
[[Jets7.1 _OldKiwi| Solution to 7.1]]
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[[Jets7.2 _OldKiwi| Solution to 7.2]]
  
 
[[Jets7.3 _OldKiwi| Solution to 7.3]]
 
[[Jets7.3 _OldKiwi| Solution to 7.3]]
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[[Jets7.4 _OldKiwi| Solution to 7.4]]
  
 
[[Jets7.5 _OldKiwi| Solution to 7.5]]
 
[[Jets7.5 _OldKiwi| Solution to 7.5]]
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[[Jets7.7 _OldKiwi| Solution to 7.7]]
 
[[Jets7.7 _OldKiwi| Solution to 7.7]]
  
8.<math>(\Rightarrow)</math> First we apply Tchebyshev to <math>E_n</math> and find that
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[[Jets7.8 _OldKiwi| Solution to 7.8]]
 
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<math> (n-1)\left|\{x \in X \mid |f(x)| \geq n-1 \}\right| \leq \int_{E_n}|f|</math>
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or rather
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<math>(n-1) m(E_n) \leq \int_{E_n}|f|</math>
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Since we have that <math>m(E_n)</math> is finite we can move it to the other side of the inequality.
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<math>nm(E_n) \leq \int_{E_n}|f| + m(E_n)</math>
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Since this is true for all <math>n</math> we take sums on both sides and note that the <math>E_n</math> are disjoint.
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<math>\sum_{n=1}^{\infty}nm(E_n) \leq \sum_{n=1}^{\infty}\int_{E_n}|f| + \sum_{n=1}^{\infty}m(E_n)</math>
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or
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<math>\sum_{n=1}^{\infty}nm(E_n)\leq \int_{X}|f| + m(X)</math>
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And we are in a finite measure space so <math>m(X) < \infty</math> and since <math>f \in L^1</math> we have <math>\int_{X}|f| < \infty</math>.
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Thus we have that  <math>\sum_{n=1}^{\infty}nm(E_n) < \infty</math>.
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<math>(\Leftarrow)</math> Since <math>|f|< n</math> in each <math>E_n</math> we have that
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<math>\int_X|f| = \sum_{n=1}^{\infty}\left(\int_{E_n}|f|\right) \leq \sum_{n=1}^{\infty}\left( n m(E_n)\right)< \infty</math>
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In other words, <math> f \in L^1</math>.
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Latest revision as of 17:17, 11 July 2008

Solution to 7.1

Solution to 7.2

Solution to 7.3

Solution to 7.4

Solution to 7.5

Solution to 7.6

Solution to 7.7

Solution to 7.8

Alumni Liaison

Correspondence Chess Grandmaster and Purdue Alumni

Prof. Dan Fleetwood