Library · Geometric Probability · Chapter 39

Expected absolute y-coordinate in a disc

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Problem 39.1

Let P=(X,Y)P = (X, Y) be a point chosen uniformly at random in the closed unit disc. What is the expected value of ∣Y∣|Y|?

Solution. Compute the integral directly in polar coordinates. For PP uniform in the unit disc, Y=Rsin⁡ΘY = R \sin \Theta where RR has density 2r2 r on [0,1][0, 1] and Θ\Theta is uniform on [0,2π)[0, 2\pi), independently of RR.

Thus E[∣Y∣]=E[R]⋅E[∣sin⁡Θ∣].\mathbb{E}[|Y|] = \mathbb{E}[R] \cdot \mathbb{E}[|\sin \Theta|]. The first factor: E[R]=∫01r⋅2r dr=23\mathbb{E}[R] = \int_0^1 r \cdot 2r \, dr = \tfrac{2}{3}. The second factor: E[∣sin⁡Θ∣]=12π∫02π∣sin⁡θ∣ dθ=42π=2π\mathbb{E}[|\sin \Theta|] = \frac{1}{2\pi} \int_0^{2\pi} |\sin \theta| \, d\theta = \frac{4}{2\pi} = \frac{2}{\pi}. Multiplying, E[∣Y∣]=23⋅2π=43π≈0.424.■\boxed{\mathbb{E}[|Y|] = \frac{2}{3} \cdot \frac{2}{\pi} = \frac{4}{3\pi} \approx 0.424.} \qedhere

The quantity E[∣Y∣]\mathbb{E}[|Y|] is the expected perpendicular distance from a uniform random point in the disc to the horizontal diameter. It also equals the projected mean absolute deviation along any fixed direction, by the rotational symmetry of the disc.

There is a clean slicing identity behind this. For a convex body KK of area A(K)A(K) in the plane, a unit direction n\mathbf{n}, and a reference level mm, let ℓK(t)\ell_K(t) be the length of the slice {P∈K:n⋅P=t}\{P \in K : \mathbf{n} \cdot P = t\}. Then the mean absolute deviation of the coordinate n⋅P\mathbf{n} \cdot P about mm is EP∼K[ ∣n⋅P−m∣ ]=1A(K)∫∣t−m∣ ℓK(t) dt.\mathbb{E}_{P \sim K}\bigl[\,|\mathbf{n} \cdot P - m|\,\bigr] = \frac{1}{A(K)} \int |t - m|\, \ell_K(t)\, dt. For the unit disc with m=0m = 0, A=πA = \pi, and ℓ(t)=21−t2\ell(t) = 2\sqrt{1 - t^2}, this evaluates to 1π∫−11∣t∣ 21−t2 dt=4/(3π)\tfrac1\pi \int_{-1}^{1} |t|\, 2\sqrt{1 - t^2}\, dt = 4/(3\pi), recovering the answer above. (Note the absolute value: the signed deviation about the mean averages to 00. For this symmetric disc the mean and median both equal 00, but a median does not generally have this property. The quantity here is the mean absolute deviation.)

import numpy as np
r = np.sqrt(np.random.rand(10**7))
theta = np.random.rand(10**7) * 2*np.pi
y = r * np.sin(theta)
print(f"sim: {np.abs(y).mean():.5f}   exact: {4/(3*np.pi):.5f}")
# sim: 0.42438   exact: 0.42441
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