How to Calculate the Standard Deviation

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Standard Deviation Calculator

Enter your dataset to calculate variance and standard deviation instantly.

Please enter a valid list of numbers separated by commas or spaces.
Standard Deviation:
Variance:
Mean (Average):
Count (n):
Sum:

What is Standard Deviation?

Standard deviation is a statistical measure that quantifies the amount of variation or dispersion in a set of values. A low standard deviation indicates that the data points tend to be close to the mean (average), while a high standard deviation indicates that the data points are spread out over a wider range of values.

The Difference Between Sample and Population

When calculating standard deviation, it is crucial to know if you are working with a Population or a Sample:

  • Population: Use this if your dataset includes every member of the group you are studying (e.g., the heights of every student in a specific classroom).
  • Sample: Use this if your dataset is a subset of a larger population (e.g., the heights of 10 random students from a whole school). The calculation for a sample uses "n-1" (Bessel's correction) to account for potential bias.

How to Calculate Standard Deviation Manually

To find the standard deviation, follow these five steps:

  1. Find the Mean: Add all numbers together and divide by the count.
  2. Subtract the Mean: Subtract the mean from each individual data point.
  3. Square the Results: Square each of the differences found in step 2.
  4. Find the Variance: For population, find the average of those squared differences. For sample, divide the sum of squared differences by (n – 1).
  5. Square Root: Take the square root of the variance to get the standard deviation.

Example Calculation

Dataset: 2, 4, 4, 4, 5, 5, 7, 9

1. Sum = 40 | Count = 8
2. Mean = 40 / 8 = 5
3. Squared Differences: (2-5)²=9, (4-5)²=1, (4-5)²=1, (4-5)²=1, (5-5)²=0, (5-5)²=0, (7-5)²=4, (9-5)²=16
4. Sum of Squares = 9+1+1+1+0+0+4+16 = 32
5. Sample Variance = 32 / (8-1) = 4.57
6. Sample SD = √4.57 = 2.138
function calculateSD() { var input = document.getElementById("dataInput").value; var errorDiv = document.getElementById("sdError"); var resultsDiv = document.getElementById("sdResults"); // Parse input var numbers = input.split(/[,\s]+/).filter(function(item) { return item.trim() !== "" && !isNaN(parseFloat(item)); }).map(Number); if (numbers.length < 2) { errorDiv.style.display = "block"; resultsDiv.style.display = "none"; return; } else { errorDiv.style.display = "none"; } var isSample = document.querySelector('input[name="sdType"]:checked').value === "sample"; var n = numbers.length; // Calculate Mean var sum = 0; for (var i = 0; i < n; i++) { sum += numbers[i]; } var mean = sum / n; // Calculate Variance var sumSqDiff = 0; for (var j = 0; j < n; j++) { sumSqDiff += Math.pow(numbers[j] – mean, 2); } var variance; if (isSample) { variance = sumSqDiff / (n – 1); } else { variance = sumSqDiff / n; } var standardDeviation = Math.sqrt(variance); // Display Results document.getElementById("resSD").innerHTML = standardDeviation.toFixed(4); document.getElementById("resVar").innerHTML = variance.toFixed(4); document.getElementById("resMean").innerHTML = mean.toFixed(4); document.getElementById("resCount").innerHTML = n; document.getElementById("resSum").innerHTML = sum.toFixed(2); resultsDiv.style.display = "block"; }

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