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UA MATH564 概率论 QE练习题6

發(fā)布時間:2025/4/14 24 豆豆
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UA MATH564 概率論 QE練習(xí)題6

  • 第二題
  • 第三題

這是2016年5月的2-3題。

第二題


Part a
Denote O as center of the circle. Randomly choose point Don the unit circle and represent points A,B,C using the center angle counterclockwise from OD to OA,OB,OC and denote as XA,XB,XCX_A,X_B,X_CXA?,XB?,XC? and XA,XB,XC~iidU[?π,π]X_A,X_B,X_C \sim_{iid} U[-\pi,\pi]XA?,XB?,XC?iid?U[?π,π]. The paths from A to B can be counterclockwise or clockwise and the distance is ∣XA?XB∣|X_A - X_B|XA??XB? or 2π?∣XA?XB∣2\pi - |X_A - X_B|2π?XA??XB?. Denote Y=∣XA?XB∣Y = |X_A - X_B|Y=XA??XB?. The minimal distribution is given by
d1=min?(Y,2π?Y)d_1 = \min(Y,2\pi - Y)d1?=min(Y,2π?Y)

Compute the distribution of XA?XBX_A - X_BXA??XB?,
P(XA?XB≤x)=P(XA≤XB+x)=∫?ππdxB∫?πxB+x14π2dxA=x+π2πP(X_A - X_B \le x) = P(X_A \le X_B + x) = \int_{-\pi}^{\pi}dx_B \int_{-\pi}^{x_B+x} \frac{1}{4\pi^2}dx_A = \frac{x+\pi}{2\pi}P(XA??XB?x)=P(XA?XB?+x)=?ππ?dxB??πxB?+x?4π21?dxA?=2πx+π?

So XA?XB~U[?π,π]?Y~U[0,π]X_A - X_B \sim U[-\pi,\pi] \Rightarrow Y \sim U[0,\pi]XA??XB?U[?π,π]?YU[0,π],
P(d≤x)=1?P(min?(Y,2π?Y)>x)=1?P(Y>x)P(2π?Y>x)=1?π?xπ=xπP(d \le x) = 1 - P(\min(Y,2\pi - Y)>x) \\ = 1-P(Y>x)P(2\pi - Y>x) = 1- \frac{\pi - x}{\pi} = \frac{x}{\pi}P(dx)=1?P(min(Y,2π?Y)>x)=1?P(Y>x)P(2π?Y>x)=1?ππ?x?=πx?

Part b
To make the center of the circle included in the triangle ABC, given minimal distance of AB is xxx, C is restricted on the arc centrosymmetric with arc AB about the center. So the probability of center being covered is
x2π\(zhòng)frac{x}{2\pi}2πx?

Part c
Denote the event center being covered as SSS, and we have
P(S∣d=x)=x2πP(S)=E[P(S∣d)]=E[X2π]=1/4P(S|d=x) = \frac{x}{2\pi} \\ P(S) = E[P(S|d)] = E[\frac{X}{2\pi}] = 1/4P(Sd=x)=2πx?P(S)=E[P(Sd)]=E[2πX?]=1/4

Notice
If XA,XB,XCX_A,X_B,X_CXA?,XB?,XC? and XA,XB,XC~iidU[0,2π]X_A,X_B,X_C \sim_{iid} U[0,2\pi]XA?,XB?,XC?iid?U[0,2π], compute the distribution of XA?XBX_A - X_BXA??XB?,
P(XA?XB≤x)=P(XA≤XB+x)=∫02πdxB∫0xB+x14π2dxA=x+π2πP(X_A - X_B \le x) = P(X_A \le X_B + x) = \int_{0}^{2\pi}dx_B \int_{0}^{x_B+x} \frac{1}{4\pi^2}dx_A = \frac{x+\pi}{2\pi}P(XA??XB?x)=P(XA?XB?+x)=02π?dxB?0xB?+x?4π21?dxA?=2πx+π?

We can get the same answer.

第三題


Let X1=1X_1 = 1X1?=1 denote the event that the first flip lands Head while X1=0X_1 = 0X1?=0 denote the event that the first flip lands Tail.
Part a
Only if the first flip lands Tail, then last flip lands Head. So the probability of the event that the last flip lands Head is
P(X1=0)=1?pP(X_1 = 0) = 1-pP(X1?=0)=1?p

Part b
Conditioning on the the first flip being a head, the next k?1k-1k?1 flips are head and the last flip is tail, so
P(X?1=k∣X1=1)=pk?1(1?p)P(X-1=k|X_1 = 1) = p^{k-1}(1-p)P(X?1=kX1?=1)=pk?1(1?p)

So X?1∣X1=1~Geo(1?p)X-1|X_1=1 \sim Geo(1-p)X?1X1?=1Geo(1?p)

Part c
Similarly, P(X?1=k∣X1=0)=(1?p)k?1pP(X-1=k|X_1 = 0) = (1-p)^{k-1}pP(X?1=kX1?=0)=(1?p)k?1p, X?1∣X1=0~Geo(p)X-1|X_1=0\sim Geo(p)X?1X1?=0Geo(p). So
E[X?1∣X1=1]=1p,E[X?1∣X1=0]=11?pE[X]=E[X?1]+1=1+1?pp+p1?pE[X-1|X_1=1] = \frac{1}{p},\ E[X-1|X_1 = 0] = \frac{1}{1-p} \\ E[X] = E[X-1]+1 = 1 + \frac{1-p}{p}+\frac{p}{1-p}E[X?1X1?=1]=p1?,?E[X?1X1?=0]=1?p1?E[X]=E[X?1]+1=1+p1?p?+1?pp?

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