Attribute Sampling Deviation Rate Size Computation
Compute the exact attribute-sampling deviation rate from a sample and deviation count and compare it with a caller-supplied tolerable rate.
Description
An observed attribute-sampling deviation rate is the fraction of examined items with recorded deviations.
An observed attribute-sampling deviation rate is the fraction of examined items with recorded deviations.1
This tool compares that observed percentage with a supplied tolerance without designing a sample or calculating a confidence bound.
When to use Attribute Sampling Deviation Rate Size Computation
Use this tool to compare that observed percentage with a supplied tolerance without designing a sample or calculating a confidence bound.
How to use Attribute Sampling Deviation Rate Size Computation and how it works
- Establish the observations, units, reference context and assumptions described below.
- Enter deviations, sampleSize, tolerableDeviationRatePercent and run the tool.
- Read deviationRatePercent, sampleSize, withinTolerableRate using the meanings and sign conventions below.
- Correct any rejected inputs and rerun; independently review the result under the stated scope.
| Input field | Meaning | Value type | Requirement |
|---|---|---|---|
| deviations | Safe-integer observed deviation count from zero through sample size. | integer | Required; finite; safe integer; minimum 0; branch conditions below |
| sampleSize | Positive safe-integer examined sample count; not a prospective size request. | integer | Required; finite; safe integer; minimum 1; branch conditions below |
| tolerableDeviationRatePercent | Caller-established observed-rate tolerance from 0 to 100 percent inclusive. | number | Required; finite; minimum 0; maximum 100; branch conditions below |
Supply safe-integer sample size at least one and safe-integer deviations from zero through sample size. Supply tolerable observed deviation percent from zero to 100. Compute 100*deviations/sampleSize and return it, the sample size and whether rate<=tolerance. Equality passes; the calculation contains no sampling-risk adjustment, confidence limit or prospective sample-size design.
observedRatePercent=100*deviations/sampleSize; within=(ratePercent<=tolerablePercent) Use the stated ordering, units and branch conditions.
| Output field | Meaning | Value type |
|---|---|---|
| deviationRatePercent | Observed sample deviation percentage; no confidence or sampling-risk adjustment. | number |
| sampleSize | Sample Size, using the scope, ordering and rule explained above. | number |
| withinTolerableRate | True when observed rate is at most the caller tolerance. | boolean |
{
"input": {
"deviations": 3,
"sampleSize": 50,
"tolerableDeviationRatePercent": 5
},
"output": {
"deviationRatePercent": 6,
"sampleSize": 50,
"withinTolerableRate": false
}
}Limitations and assumptions
The result summarizes supplied audit observations under the stated arithmetic or checklist rule. It does not inspect underlying documents, select sufficient audit evidence, make a professional assurance judgment or establish regulatory compliance. Empty or all-true input can describe only the recorded assertions.
Supply explicit values and dense aligned arrays. Unexpected fields, wrong types and nonfinite scalar values are rejected; fixed-token, alignment and other branch conditions are explained above. A successful false flag, empty match list or unknown-evidence list differs from an input error. Extremely large inputs or nonrepresentable results may fail.
Alternative or Complementary methods
Use Sampling Size Estimation Calculator for a related operation: Estimating a population mean requires a precision target, variability estimate and sampling model.
Use Block Stratified Selection Coverage Adequacy Checker for a related operation: Stratified coverage must be considered by block as well as in aggregate.
References
Similar or alternative tools
- Sampling Size Estimation Calculator
Estimating a population mean requires a precision target, variability estimate and sampling model.
- Block Stratified Selection Coverage Adequacy Checker
Stratified coverage must be considered by block as well as in aggregate.