Standard Deviation Calculator

Quickly measure how tightly your numbers cluster around the average and decide whether the variation you see is expected or worth investigating.

Before You Calculate

Paste your values using commas, spaces, or line breaks-whatever is easiest to copy from your source.
Strip away non-numeric characters (units, percent signs) so the parser only processes numbers.
Make sure you are analysing a single variable; mixing measurements with different meanings will distort the spread.

Mean and median: Quick markers that reveal skew or balance.

Population standard deviation: Shows the average distance from the mean when you treat the dataset as complete.

Variance, range, and count: Extra context so you can quote variability and sample size together.

Scan the sorted output for outliers and rerun the calculation with and without them.
Repeat the calculation after filtering groups or time ranges to see how volatility changes.
Log the result alongside the date and dataset label so you can track trends over time.

Use the statistic to spot stability, volatility, or inconsistency depending on the context of your work.

Quality control: Monitor production lines by comparing the latest spread against historic batches.
Finance: Evaluate how far returns swing from their average to understand portfolio risk.
Research: Pair deviation with confidence intervals to judge whether two groups truly differ.

Keep a simple log of similar datasets so you can compare today'''s spread against historical baselines.

If measurements use different units or scales, convert them first; mixing seconds with milliseconds will inflate the deviation.

Translate the number into plain language. For example: "Scores vary by about 4 points, so most students cluster between 76 and 84."

Include count and range alongside deviation so stakeholders understand the sample size behind the metric.