Beta Function Calculator

Calculate the beta function B(x,y) with step-by-step solutions using gamma function relationships

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B(x, y) = Γ(x)Γ(y) / Γ(x+y)

Integral form: B(x, y) = ∫₀¹ t^(x-1)(1-t)^(y-1) dt

Both x and y must be positive real numbers (> 0)

Quick Examples

Invalid Input

Both x and y must be positive real numbers (greater than 0).

B(, )

= Γ()Γ() / Γ()

Γ()

Γ()

Γ()

Reciprocal 1/B(x,y)

Log Beta ln(B(x,y))

Step-by-Step Solution

1

Identify the input values

x = , y =

2

Calculate Gamma function values

Γ() =
Γ() =
Γ() =

3

Apply the Beta function formula

B(x, y) = Γ(x)Γ(y) / Γ(x+y)

4

Result

B(, ) = × / =

Beta Function Properties

Symmetry

B(x, y) = B(y, x)

Recurrence

B(x+1, y) = B(x,y) × x/(x+y)

Special Value

B(1/2, 1/2) = π

For Integers

B(m,n) = (m-1)!(n-1)!/(m+n-1)!

Special Values Reference

x y B(x, y) Notes
1 1 1 Base case
1/2 1/2 π ≈ 3.14159 Famous special value
2 3 1/12 ≈ 0.0833 = 1!×2!/4!
3 4 1/60 ≈ 0.0167 = 2!×3!/6!
1 n 1/n Simple reciprocal

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About Beta Function Calculator

What is the Beta Function?

The Beta function B(x, y), also called Euler's integral of the first kind, is a fundamental mathematical function that takes two positive real numbers as arguments and produces a real number.

Mathematical Definition

The Beta function is defined by the integral:

B(x, y) = ∫₀¹ t^(x-1)(1-t)^(y-1) dt

Relation to Gamma Function

The Beta function can be expressed in terms of the Gamma function:

B(x, y) = Γ(x)Γ(y) / Γ(x+y)

For positive integers:

B(p, q) = (p-1)!(q-1)! / (p+q-1)!

Key Properties

Symmetry Property

B(x, y) = B(y, x)

The order of arguments doesn't affect the result.

Recurrence Relations

  • B(x+1, y) = B(x, y) × x/(x+y)
  • B(x, y+1) = B(x, y) × y/(x+y)
  • B(x+1, y) + B(x, y+1) = B(x, y)

Special Values

  • B(1, 1) = 1
  • B(1/2, 1/2) = π
  • B(1, n) = 1/n
  • B(m, n) = 1/(m × C(m+n-1, n-1)) where C is the binomial coefficient

Trigonometric Form

B(x, y) = 2 ∫₀^(π/2) (sin θ)^(2x-1)(cos θ)^(2y-1) dθ

Applications

  1. Probability and Statistics - Central to the Beta distribution
  2. Bayesian Inference - Prior and posterior distributions
  3. Combinatorics - Related to binomial coefficients
  4. Physics - String theory scattering amplitudes
  5. Machine Learning - Beta-binomial models, Dirichlet distributions

Relation to Binomial Coefficients

B(m, n) = 1 / (n × C(m+n-1, m-1))

where C(n, k) is the binomial coefficient "n choose k".

Common Mistakes

  1. Confusing with Beta distribution - B(x,y) is the function, Beta(α,β) is the probability distribution that uses it
  2. Forgetting symmetry - B(2,3) = B(3,2)
  3. Invalid inputs - Both x and y must be positive real numbers