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Hoeffding’s inequality

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8/10 is 8 heads in each 10 times. This is qite rare . 80% of the heads are in 99.9%. The red is the area. t≧0 In this case, t is 0.8, and -t is 0.2. They are symmetry. 1/100 is the possibilty to have 80% of the head. This is very difficlt like finding rich men . Var(Z)<∞ ∴ You may know Bernoulli trial. n=10, and k=8. P(X=8)=0.044≒4/100. Therefore, you may have 1~4 of (8/10) heads in each 100 times .You can't predict anything because of Zero.

Central limit theorem

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Whenever you toss your coins, you are close to normal distribution. You can see Gaussian function . μ is the average, and σ^2 is the distribution. Y is E(X) . I tossed coins 100 times. NORMDIST(x,0.5,(x-0.5)^2,0) You may have 80% of the head once (1.7%). When you are around Y which is the average, it is almost Zero. You need to go far beyond that. It is quite rare.0.5 is null, and 0.8 and 0.2 are symmetry. NORMDIST(0.8,0.5,(0.8-0.5)^2,1)≒0.999 X=0.6 is 100% The average is normal and Zero, but 9/10 and 10/10 is the difficulty. It is narrower and close to Zero. You may talk about singularity.

Markov’s Inequality

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It is hard to see rich men. This is called Markov’s Inequality. E[X] is the average , although I don't reach it. X is a discrete random variable. ∴ a>0

Gaussian function

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This is an even function which is symmetry by the Y-axis. ∴ This is the inflection point. You still see the square . f(0)=1 The average is the top which is called normal distribution. μ is the average, and σ^2>0. R=(-∞,∞)

Euclidean distance

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This is taxicab geometry. You move from X to Y. Each square is 1. Red:1+2+2+1+2+2=10 Green:5+5=10 They are the same line. This is called Manhattan distance. n is the dimension. Then, this is Euclidean norm. This is 1*1 squares. ∴ There are 25 suares, so K=25. √50≒7.07. 50=5^2+5^2. This is the green.

Approximate Carathéodory’s Theorem

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Higher dimensions are chaotic . However, you close to Zero, although you keep expanding. This is almost 1-1=0. k go to ∞, which is called Euclidean norm. Then you pile squares . They are almost circles, and cubes are also balls. They are closed. However, higher dimensions are opened, so they are chaotic.

The empirical method of Maurey

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It is hard to define boundary mathematically. Zeta function is well known . ζ(s)=0 You need to fill all spaces for integration. A⊂R^d x is the convex hull of A. When λn, n>d+1. Then, n-1 go to 0. x2-x1=0.00000000000000000009. μ is the vector. x1 x2 ・・・・ xn λ1(0.9) λ11(0.00000000009) λ2(0.09) λ12(0.000000000009) λ3(0.009) λ13(0.0000000000009) λ4(0.0009) λ14(0.00000000000009) λ5(0.00009) λ15(0.000000000000009) λ6(0.000009) λ16(0.0000000000000009) λ7(0.0000009) λ17(0.00000000000000009) ...

Van Aubel's theorem

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Each square is connected, and the center is lined. PR and SQ is vertical, and they are symmetry. AB=2a, BC=2b, CD=2c, DA=2d, and they are complex numbers. 2a+2b+2c+2d=0 ∴ a+b+c+d=0 You see the complex number, so A=0. Then, AP=p is z. ∴ p=a+ia=(1+i)a You see Euler's formula . π/2=90° Then, you turn around squares. SQ=A and PR=B B=iA iB=i^2A ∴ A+iB=0 Squares are curved.