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Rayleigh Distribution Calculator

Free Rayleigh distribution calculator. Compute PDF, CDF, P(X≤x), P(a≤X≤b), mean, median, mode, varia

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How: Enter inputs and compute results.

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STATISTICSDistributions

Rayleigh Distribution — Magnitude of 2D Gaussian Vectors

Wind speed, wave height, wireless fading. From 2D Gaussian components to real-world magnitude modeling. PDF, CDF, percentiles, P(a≤X≤b).

Real-World Scenarios — Click to Load

Input Parameters

PDF with P(a≤X≤b) Shaded

rayleigh_results.sh
CALCULATED
$ rayleigh --sigma=1 --x=1
Mean
1.2533
Median
1.1774
Mode
1.0000
Variance
0.4292
P(X≤1)
39.3469%
P(0≤X≤2)
86.4665%
25th %ile
0.7585
50th %ile
1.1774
75th %ile
1.6651
95th %ile
2.4477
Share:
Rayleigh Distribution Rayleigh(σ=1)
P(X≤1) = 39.35%
P(0≤X≤2) = 86.47%
Mean = 1.253Mode = 1.000Variance = 0.429
numbervibe.com/calculators/statistics/rayleigh-distribution-calculator

Moments Comparison

Percentiles

Calculation Breakdown

MOMENTS
Mean
1.2533
σ√(π/2) = 1×√(π/2)
Median
1.1774
σ√(2ln2) ≈ 1.1774σ
Mode
1.0000
σ = 1
Variance
0.4292
σ²(4-π)/2 ≈ 0.4292σ²
P(X≤x)
39.3469%
1 - exp(-x²/(2σ²))
P(a≤X≤b)
86.4665%
F(b) - F(a)

For educational and informational purposes only. Verify with a qualified professional.

Key Takeaways

  • The Rayleigh distribution models the magnitude of a 2D vector whose components are independent N(0,σ²)
  • PDF: f(x) = (x/σ²) × exp(-x²/(2σ²)) for x ≥ 0; CDF: F(x) = 1 - exp(-x²/(2σ²))
  • Mean = σ√(π/2) ≈ 1.2533σ, Median = σ√(2ln2) ≈ 1.1774σ, Mode = σ
  • Variance = σ²(4-π)/2 ≈ 0.4292σ²
  • P(a ≤ X ≤ b) = exp(-a²/(2σ²)) - exp(-b²/(2σ²)); Percentile q: x_q = σ√(-2ln(1-q))

Did You Know?

📡Rayleigh fading models wireless signal strength when there is no line-of-sight — multipath scatteringSource: IEEE
🌬️Wind speed magnitude (2D wind vector) is often modeled with Rayleigh when components are GaussianSource: Meteorology
🌊Wave heights in oceanography can follow Rayleigh when wave components are GaussianSource: Oceanography
🎯Radial error in 2D shooting (x,y independent Gaussian) follows Rayleigh — used in ballisticsSource: Ballistics
📶Signal strength in fading channels — Rayleigh is the classic model for non-LOS propagationSource: Wireless
📐Rayleigh is a special case of Weibull with shape parameter k=2Source: MathWorld

How It Works

1. 2D Gaussian Magnitude

If Z₁, Z₂ ~ N(0,σ²) independent, then X = √(Z₁² + Z₂²) ~ Rayleigh(σ).

2. PDF and CDF

PDF f(x)=(x/σ²)exp(-x²/(2σ²)) peaks at x=σ. CDF F(x)=1-exp(-x²/(2σ²)) has closed form.

3. Mean, Median, Mode

Mean > Median > Mode (right-skewed). Mode = σ is the peak. Mean = σ√(π/2) ≈ 1.253σ.

4. Wireless Applications

Rayleigh fading: when signal arrives via many paths with random phase, no dominant component.

5. Percentiles

The q-th percentile is x_q = σ√(-2ln(1-q)). Median = σ√(2ln2).

Expert Tips

Rayleigh vs Rice

When there is a dominant (line-of-sight) component, use Rice distribution. Rayleigh = Rice with zero dominant.

σ Interpretation

σ is the scale. Larger σ = more spread, higher mean. Mode = σ always.

Weibull Connection

Rayleigh(σ) = Weibull(shape=2, scale=σ√2). Weibull generalizes Rayleigh.

Chi-Square Link

If X ~ Rayleigh(σ), then X²/(2σ²) ~ Exp(1). Squared Rayleigh relates to exponential.

Why Use This Calculator vs Other Tools?

FeatureThis CalculatorExcelR/Python
PDF + CDF + Percentiles❌ No built-in⚠️ Package needed
P(a≤X≤b) shaded region⚠️ Manual
7 real-world examples
Interactive charts⚠️ Requires plot
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Frequently Asked Questions

When should I use the Rayleigh distribution?

When modeling the magnitude of a 2D vector whose components are independent N(0,σ²): wind speed magnitude, signal envelope in fading, radial error in 2D, wave height.

What is the relationship to the normal distribution?

If Z₁, Z₂ ~ N(0,σ²) independent, then X = √(Z₁²+Z₂²) ~ Rayleigh(σ). Rayleigh is the distribution of the magnitude.

What is Rayleigh fading?

In wireless, when signal arrives via many scattered paths with random phase (no line-of-sight), the envelope follows Rayleigh. Classic model for fading channels.

How do I interpret σ?

σ is the scale parameter. Mode = σ. Mean = σ√(π/2) ≈ 1.253σ. Larger σ means more spread and higher values.

Rayleigh vs Rice distribution?

Rice has a dominant (line-of-sight) component; Rayleigh has none. Rayleigh = Rice with zero dominant component.

How do I fit Rayleigh to data?

MLE: σ̂ = √(Σxᵢ²/(2n)). Or use method of moments: σ̂ = x̄/√(π/2).

Rayleigh by the Numbers

σ√(π/2)
Mean ≈ 1.253σ
σ
Mode
0.429σ²
Variance
2D Gaussian
Magnitude

Disclaimer: This calculator uses exact closed-form formulas for the Rayleigh distribution. Results are mathematically exact. For critical applications (wireless system design, wind energy, structural engineering), verify assumptions (2D Gaussian components, independence). This tool is for educational and professional reference purposes.

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