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SPECIAL FUNCTIONS / GAUSSIAN INTEGRAL

Real Error Function Calculator

Evaluate erf(x), its complement, and the odd-symmetry check for a real input.

  • 01 Calculated in this tab
  • 02 Values stay in this browser tab
  • 03 Use boundary

Conversion input

Known value

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METHOD / WORKED EXAMPLE

Connect the Gaussian integral to two checkable identities

The error function accumulates a normalized exp(-t squared) integral from zero to x. Reporting erfc and odd symmetry helps detect sign or complement mistakes in downstream formulas.

WORKED DEFAULT

Check the calculation with the default inputs

For x = 1, erf(1) is approximately 0.84270079 and erfc(1) is approximately 0.15729921. Their sum is 1, while erf(-1) equals -erf(1).

  1. Enter the argumentx = 1
  2. Evaluate the integral approximationerf(1) = 0.84270079...
  3. Check the complement1 - erf(1) = 0.15729921...

READ THE RESULT

Interpret the output in context

erf is bounded between -1 and 1 for real inputs. Its numerical value becomes a normal-probability expression only after using the distribution's required square-root-of-two transformation.

ASSUMPTIONS AND LIMITS

Know where the model stops

  • x is real and finite.
  • The standard normalized error function is intended.
  • Approximation-level precision is sufficient for the calculation.

The output is a special-function approximation, not automatically a normal-distribution probability until the correct scaling and event definition are applied.

COMMON QUESTIONS

Real Error Function Calculator FAQs

Is erf(x) directly a normal cumulative probability?

Not without scaling and interpretation. The standard normal CDF satisfies Phi(z) = one half times [1 + erf(z/sqrt(2))]. Using erf(z) directly changes the argument and gives the wrong probability. Start from the exact probability event, apply the square-root-of-two transformation, and distinguish cumulative, central, and tail areas.

Why can erf be negative for a negative input?

The defining integral runs from zero to x. Reversing that direction for a negative x changes the sign while the Gaussian integrand remains positive, so erf is an odd function: erf(-x) = -erf(x). The displayed symmetry residual checks that property and can reveal accidental absolute-value or sign handling in another formula.

How accurate is the displayed error-function value?

The page uses a common finite polynomial approximation in double precision, with error suitable for ordinary educational and planning calculations but not arbitrary-precision scientific work. The identity checks test internal consistency, not absolute error against an exact integral. For stringent tolerances, validate with a certified numerical library and record its version and precision settings.

Use boundary

Calculation path

Evaluate a bounded polynomial approximation to the normalized Gaussian integral, then calculate erfc and the odd-symmetry residual as consistency checks.

Calculation path

erf(x) = (2/sqrt(pi)) integral from 0 to x of exp(-t^2) dt.