Signal Detection Theory Calculator

D-Prime Calculator

Calculate d-prime, hit rate, false alarm rate, criterion c, beta, and response bias from signal detection counts or rates. Use it for psychology experiments, perception tasks, diagnostics, and yes-no classification data.

Hits slider
0500
Misses slider
0500
False Alarms slider
0500
Correct Rejections slider
0500

Input Summary

Hit Rate: 80%
False Alarm Rate: 15%
Signal Trials: 100
Noise Trials: 100
Hit Rate Correction: Not Needed
False Alarm Correction: Not Needed

What Is D-Prime in Signal Detection Theory?

d-prime is a sensitivity score from signal detection theory. It compares the standardized hit rate with the standardized false alarm rate, so it separates actual discrimination ability from a general tendency to answer yes or no.

How to Calculate D-Prime

The standard formula is d-prime = z(H) - z(FA), where H is hit rate and FA is false alarm rate. Hit rate is hits divided by signal-present trials. False alarm rate is false alarms divided by noise-only trials.

D-Prime Interpretation Table

D-Prime Range
Meaning
Practical Reading
Below 0
Reversed or inconsistent responses
Check coding, labels, or task setup.
0 to 0.5
Near chance sensitivity
Signal and noise are hard to separate.
0.5 to 1
Weak sensitivity
Some discrimination, but not strong.
1 to 2
Moderate sensitivity
Meaningful signal detection.
2 to 3
Strong sensitivity
Clear separation between signal and noise.
3+
Very strong sensitivity
Excellent separation in many tasks.

Criterion c and Response Bias

Criterion c estimates response bias. A positive c usually means the observer is conservative and needs stronger evidence to say yes. A negative c usually means the observer is liberal and says yes more easily.

Why 0% and 100% Rates Need Correction

A hit rate of 100% or a false alarm rate of 0% produces an infinite z-score. The calculator applies correction only when a count-based rate is exactly 0% or 100%, which keeps d-prime finite without changing ordinary non-boundary rates.

Counts vs Rates Input

Use counts when you have the full signal detection table: hits, misses, false alarms, and correct rejections. Use rates when your paper, assignment, or dataset already gives hit rate and false alarm rate.

Frequently Asked Questions

What Is d'?+

d' is a signal detection theory measure of sensitivity. It estimates how well someone separates signal from noise using hit rate and false alarm rate.

How Do You Calculate d'?+

Calculate z(hit rate) and z(false alarm rate), then subtract them. Formula: d' = z(H) - z(FA). Higher values mean stronger sensitivity.

What Is a Good d' Value?+

A d' near 0 suggests chance-level sensitivity. Around 1 is modest, 2 is strong, and 3 or higher is very strong in many yes-no detection tasks.

Why Does d' Become Infinite?+

d' becomes infinite when hit rate is 100% or false alarm rate is 0% because the z-score is unbounded. A correction keeps the estimate finite.