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Bertrand Paradox Calculator

Explore Bertrand's geometric probability paradox across all three classical methods (random endpoints, random radius, random midpoint) with Monte Carlo simulation.

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What is Bertrand's Paradox in Geometric Probability?

Bertrand's Paradox is a fundamental problem in geometric probability theory introduced by Joseph Bertrand in 1889. It demonstrates that probabilities in continuous spaces are not well-defined unless the mechanism that generates random variables is specified.

The Problem Statement

Consider an equilateral triangle inscribed inside a circle. Suppose a chord of the circle is chosen "at random." What is the probability that the chord is longer than a side of the equilateral triangle?

The Three Classical Solutions

1. Method 1: Random Endpoints

Choose two independent points uniformly at random on the circumference of the circle and connect them to form a chord. The probability that the chord exceeds the side length of the inscribed equilateral triangle is:

$$P = \frac{1}{3} \approx 33.33\%$$

2. Method 2: Random Radius

Choose a radius of the circle at random, and then pick a point on that radius uniformly at random to serve as the midpoint of the chord. The probability is:

$$P = \frac{1}{2} = 50.00\%$$

3. Method 3: Random Midpoint

Choose a point uniformly at random anywhere inside the disk of the circle to serve as the midpoint of the chord. The probability is:

$$P = \frac{1}{4} = 25.00\%$$

Why is it a Paradox?

All three methods appear logically valid, yet each yields a different probability. The paradox arises because "at random" is ambiguous when choosing from an infinite continuous set of lines.

Frequently Asked Questions

Which solution to Bertrand's paradox is the correct one?

None of the three solutions is uniquely correct without specifying the physical experiment used to select random chords. Edwin Jaynes showed that Method 2 (Random Radius) satisfies maximum ignorance, rotational, and scale invariance.

Can I use this calculator for other polygon shapes?

Yes, you can set the number of polygon sides $N$ (e.g. 4 for square, 5 for pentagon) to evaluate probability thresholds for general regular $N$-gons.

How does the Monte Carlo simulation work?

The calculator runs 10,000 trials for each of the three random chord selection methods live in your browser and compares the simulated results against theoretical values.

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