The Outlier Boundary Calculator is a tool used to identify values that lie outside of the expected range for a given set of data. It uses an upper and lower boundary to define the range of values that are considered “normal” for the data and flags any values that are outside of this range as outliers. This calculator is a useful tool for identifying and detecting anomalies in data sets.
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The interquartile range, often abbreviated IQR, is the difference between the 25th percentile (Q1) and the 75th percentile (Q3) in a dataset.
We often declare an observation to be an outlier in a dataset if it has a value 1.5 times greater than the IQR or 1.5 times less than the IQR.
This calculator uses this formula to automatically calculate the upper and lower outlier boundaries for a given dataset.
Simply enter the list of the comma-separated values for the dataset, then click the “Calculate” button:
Dataset values:
Q1: 5.0000
Q3: 20.7500
Interquartile Range: 15.7500
Lower Outlier Boundary: -18.6250
Upper Outlier Boundary: 44.3750
function calc() {
var x = document.getElementById(‘x’).value.split(‘,’).map(Number);
var Q1 = jStat.percentile(x, 0.25);
var Q3 = jStat.percentile(x, 0.75);
var IQR = Q3-Q1;
var lower = Q1 – 1.5*IQR;
var upper = Q3-(-1.5*IQR);
document.getElementById(‘Q1’).innerHTML = Q1.toFixed(4);
document.getElementById(‘Q3’).innerHTML = Q3.toFixed(4);
document.getElementById(‘IQR’).innerHTML = IQR.toFixed(4);
document.getElementById(‘lower’).innerHTML = lower.toFixed(4);
document.getElementById(‘upper’).innerHTML = upper.toFixed(4);
} //end calc function