Description
Divide signedErrorSum by positive integer observationCount for meanError.
A statistic summarizes data under chosen conventions for missing values, ties, spread, and denominators. A component calculation uses the supplied values; it does not check whether the data collection or statistical model is appropriate.
Divide signedErrorSum by positive integer observationCount for meanError.
When to use this tool
Use Mean Error From Signed Sum when you need one stated statistical component with explicit handling of boundary cases.
How to use the tool and how it works
- Enter signedErrorSum, observationCount. Use the units and conventions below.
- Run the tool. Correct any format, range, or cross-field input error before interpreting the output.
- Read meanError. Use the output convention below.
Divide signedErrorSum by positive integer observationCount for meanError.1
| Input field | Meaning and units | Accepted input |
|---|---|---|
| signedErrorSum | Signed Error Sum | Required. Finite number. |
| observationCount | Observation Count | Required. Safe integer; minimum 1. |
| Output field | Interpretation | Returned shape |
|---|---|---|
| meanError | Mean Error | Required. Finite number. |
{
"input": {
"signedErrorSum": 15,
"observationCount": 6
},
"output": {
"meanError": 2.5
}
}Limitations and assumptions
- Inputs must describe the same support and error-sign convention; cancellation can hide magnitude and no MAE, variance, or missingness handling is supplied.
- Inputs must satisfy both the field types and the cross-field conditions above. Invalid input causes an error; a successful false flag or documented placeholder is a different result.
- Numeric calculations use binary floating point unless exact decimal-integer arithmetic is explicitly stated. No hidden measurement tolerance or decimal rounding is added; nonfinite or out-of-contract results are rejected. Numeric signed-zero results are exported as zero.
Alternative or Complementary methods
Inspect the data distribution and the full estimation method before drawing a statistical conclusion.
References
Similar or alternative tools
- Linearization Relative Error
Require actualValue nonzero and return abs((linearizedValue - actualValue)/actualValue).
- Mae Denominator Weight Sum
Require nonnegative weights with a positive finite sum and return weightSum.