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Standard Deviation Calculator.
Calculate population and sample standard deviation with variance
Set your values
Results update as you type.
Sample Results
Results
Sorted Data
10, 12, 16, 16, 21, 23, 23, 23
Understanding Standard Deviation
Use Cases
Analyze test scores
Teachers and students can use the calculator to understand the spread of exam results, identifying how consistent performance is across a class.
Example: Enter scores like 85, 90, 78, 92, 88 to see the standard deviation.
Quality control in manufacturing
Engineers can measure variability in product dimensions or weights to ensure consistency and meet quality standards.
Example: Input measurements like 10.2, 10.5, 10.1, 10.3 to check process variability.
Frequently Asked Questions
- What is the difference between population and sample standard deviation?
- Population standard deviation measures the spread of an entire population, using all data points. Sample standard deviation estimates the spread of a population based on a sample, using n-1 in the denominator to correct bias. Use population when you have all data, sample when you have a subset.
- How do I use the standard deviation calculator?
- Enter your data values separated by commas or spaces. The calculator will compute both population and sample standard deviation, along with variance. Ensure you enter numeric values only and separate them correctly.
- What does variance mean in statistics?
- Variance is the average of the squared differences from the mean. It measures how far each number in the set is from the mean. Standard deviation is the square root of variance, providing a measure of spread in the same units as the data.
Tips & Common Mistakes
Tips
- Ensure your data is numeric and separated by commas or spaces for accurate calculation.
- Use population standard deviation when your data represents the entire group; use sample for a subset.
- Check for outliers before interpreting standard deviation, as extreme values can inflate the result.
- Remember that standard deviation is always non-negative; a value of 0 means all data points are identical.
Common Mistakes to Avoid
- Confusing population and sample standard deviation, leading to incorrect conclusions.
- Entering non-numeric characters or mixing delimiters, causing errors in calculation.
- Using standard deviation to compare datasets with different units or scales without proper normalization.
Last updated: August 13, 2026