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Gamma Function

The Gamma function extends the factorial to real and complex numbers.
Learn the formula, key properties, and worked examples.

The Formula

Γ(n) = ∫₀^∞ t^(n−1) × e^(−t) dt

Key property: Γ(n) = (n−1)! for positive integers

The Gamma function, introduced by Swiss mathematician Leonhard Euler in the 1720s, extends the concept of the factorial to all real and complex numbers — not just positive integers. While n! is only defined for non-negative integers, Γ(n) fills in the gaps, giving meaningful values for numbers like Γ(1.5) or Γ(0.5).

The key relationship is Γ(n) = (n−1)! for positive integers. So Γ(5) = 4! = 24, Γ(6) = 5! = 120, and so on. The function shifts the argument by 1 compared to the ordinary factorial, which is a historical convention from Euler's original definition.

One of the most remarkable values is Γ(1/2) = √π ≈ 1.7725. This identity shows up throughout physics and statistics, particularly in the normalization of the Gaussian (normal) distribution. The functional equation Γ(n+1) = n × Γ(n) allows values to be computed recursively from known ones.

Variables

SymbolMeaningUnit
Γ(n)Gamma function evaluated at ndimensionless
nInput value (any real or complex number except 0 and negative integers)dimensionless
tIntegration variabledimensionless
eEuler's number ≈ 2.71828dimensionless

Example 1

Verify that Γ(5) equals 4! = 24 using the recursive property.

Start from Γ(1) = 1 (by definition, since Γ(1) = 0! = 1)

Apply Γ(n+1) = n × Γ(n) repeatedly:

Γ(2) = 1 × Γ(1) = 1 × 1 = 1

Γ(3) = 2 × Γ(2) = 2 × 1 = 2

Γ(4) = 3 × Γ(3) = 3 × 2 = 6

Γ(5) = 4 × Γ(4) = 4 × 6 = 24

Γ(5) = 24, which equals 4! ✓

Example 2

Find Γ(3/2) using the known value Γ(1/2) = √π.

Use the recursive property: Γ(3/2) = Γ(1/2 + 1) = (1/2) × Γ(1/2)

Γ(1/2) = √π ≈ 1.7725

Γ(3/2) = (1/2) × 1.7725 = 0.8862

Γ(3/2) = √π / 2 ≈ 0.8862 — this value appears in the formula for the volume of a 3D sphere

When to Use It

Use the Gamma function when:

  • Evaluating factorial-like expressions for non-integer arguments
  • Working with probability distributions such as the chi-squared, beta, and gamma distributions
  • Normalizing integrals in quantum mechanics and statistical mechanics
  • Computing volumes of n-dimensional spheres (hyperspheres)
  • Solving differential equations and integrals in advanced physics and engineering

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