Weber Fraction
Calculate the dimensionless Weber fraction as measured just-noticeable increment divided by baseline stimulus magnitude. Both magnitudes must use the same linear units; no universal sensory threshold is assumed.
Description
The Weber fraction expresses a measured just-noticeable increment relative to a baseline stimulus.
The Weber fraction expresses a measured just-noticeable increment relative to a baseline stimulus. Both quantities need the same linear unit basis.1
Calculate the dimensionless Weber fraction as measured just-noticeable increment divided by baseline stimulus magnitude. Both magnitudes must use the same linear units; no universal sensory threshold is assumed.
When to use Weber Fraction
Use this tool to calculate the dimensionless Weber fraction as measured just-noticeable increment divided by baseline stimulus magnitude. Both magnitudes must use the same linear units; no universal sensory threshold is assumed.
Prepare the task-specific rates, comparable response-time means, identified spike train, processed ERP or estimated spectra requested. Confirm units, preprocessing, sample pairing and caller-fitted model coefficients.
How to use Weber Fraction and understand its results
- Prepare the task-specific rates, comparable response-time means, identified spike train, processed ERP or estimated spectra requested. Confirm units, preprocessing, sample pairing and caller-fitted model coefficients.
- Enter justNoticeableIncrement, baselineMagnitude using the field table and calculation rules, then run the tool.
- Read weberFraction. The explanation below defines the units, signs, ordering and any flags or placeholder values.
- If the tool reports an input issue, correct the values and run it again. Apply the stated assumptions when interpreting a successfully returned result.
| Input field | Meaning | Value type; see rules below | Requirement |
|---|---|---|---|
| justNoticeableIncrement | Measured just-noticeable increment in linear stimulus units. | number; minimum: 0 | Required |
| baselineMagnitude | Positive baseline stimulus in the same linear units. | number; strictly above: 0 | Required |
Enter nonnegative measured increment and strictly positive baseline. Return their dimensionless quotient. A zero increment gives zero.
weberFraction=justNoticeableIncrement/baselineMagnitude Units, indexing, boundary conditions and exceptional cases are defined in the calculation rules above.
| Output field | Meaning | Value type |
|---|---|---|
| weberFraction | Just-noticeable increment divided by baseline magnitude. | number; minimum: 0 |
{
"input": {
"justNoticeableIncrement": 5,
"baselineMagnitude": 100
},
"output": {
"weberFraction": 0.05
}
}Limitations and assumptions
The tool does not measure a threshold or establish that Weber scaling holds for the sensory task. Logarithmic units must be converted appropriately before division.
Numeric inputs must be finite. Follow the calculation-specific rules for overflow, underflow and exceptional cases. Missing required fields, extra fields, wrong value types and violations of the calculation rules are input errors.
Alternative or Complementary methods
Use Weber Law Just Noticeable Difference: Evaluate Weber law ΔS = k × S from a supplied Weber fraction and positive baseline magnitude in linear units. Applicability of the fraction to the sensory task belongs to the caller. For a complementary task, use Hick Choice Reaction Time: Evaluate the equally likely choice form RT = a + b × log2(n), using caller-fitted coefficients in milliseconds. Predictions must be nonnegative; this is a model evaluation without participant calibration.
References
-
Weber Fraction — tool.io
Similar or alternative tools
- Weber Law Just Noticeable Difference
Evaluate Weber law ΔS = k × S from a supplied Weber fraction and positive baseline magnitude in linear units. Applicability of the fraction to the sensory task belongs to the caller.
- Hick Choice Reaction Time
Evaluate the equally likely choice form RT = a + b × log2(n), using caller-fitted coefficients in milliseconds. Predictions must be nonnegative; this is a model evaluation without participant calibration.