- What is the error function and why would I use it on a spreadsheet?
- The error function (ERF) quantifies the probability that a measurement or value from a normal distribution falls within a given tolerance band. In supply chain, it's used to evaluate measurement accuracy, forecast reliability, and quality acceptance rates.
- Can ERF handle negative numbers?
- ERF mathematically accepts negative values and is symmetric around zero, so ERF(−x) = −ERF(x). However, in stock-take contexts (quantities, tolerances), inputs are typically positive. If you need to work with deviations around a mean, you'd usually work with absolute values or standardized scores first.
- What's the difference between ERF and NORM.S.DIST?
- ERF directly returns the cumulative probability for a standardized normal distribution (mean 0, std dev 1/√2). NORM.S.DIST is more general and lets you specify any mean and standard deviation, so it's more flexible for real-world data. Use NORM.S.DIST if you're analyzing non-standardized measurements.
- Why does ERF(1) give roughly 0.8427 instead of a round number?
- ERF returns the exact probability from the mathematical error function. The value 0.8427 means that ~84.3% of values in a normal distribution fall within one standard deviation of the mean—a fundamental property of statistics, not a rounding issue.