Statistics formula reference

Logistic Sigmoid

Maps a real-valued score to a number between zero and one.

Open in editor
LaTeX\sigma(z)=\frac{1}{1+e^{-z}}

Variables

  • z: linear predictor
  • σ(z): transformed value

How to use this formula

Maps a real-valued score to a number between zero and one.

Important notes

  • A probability interpretation depends on the model and calibration.

Quick example

At z=0, σ(z)=0.5.

Applicability, worked calculation, and verification

Assumptions and domain checks

  • A probability interpretation depends on the model and calibration.
  • For the Logistic Sigmoid, every denominator must be nonzero, and the numerator and denominator must remain correctly grouped.
  • For the Logistic Sigmoid, identify whether each quantity is a sample statistic, population parameter, estimator, or model value, and check the method assumptions.

Worked example

Input

Output

At z=0, σ(z)=0.5.

Common mistakes

  • When copying Logistic Sigmoid, keep the complete numerator and denominator grouped; a missing brace or parenthesis changes the result.
  • For the Logistic Sigmoid, do not interpret a descriptive statistic as a causal or population conclusion without the sampling and model assumptions.

Continue the workflow

Use Logistic Sigmoid in your own work

  1. Check the domainMatch the variables and assumptions to the problem before substituting values.
  2. Copy the exact notationPreserve grouping, signs, and exponents in \sigma(z)=\frac{1}{1+e^{-z}}.
  3. Edit or convertOpen the expression in the LaTeX editor, then export it for your document or web page.

Review and verification

Last reviewed: 2026-07-23

Automated quality check: Kept noindex until the missing evidence is supplied.

Formula references

Frequently asked questions

What is the Logistic Sigmoid used for?

Maps a real-valued score to a number between zero and one.

Can I copy this formula as LaTeX?

Yes. Copy \sigma(z)=\frac{1}{1+e^{-z}} or open it in the LaTeX editor.

What should I check before using it?

Confirm that each variable, unit, domain restriction, and assumption matches the problem.

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