Standard Deviation Calculator
Calculate population & sample standard deviation, variance, and other statistical measures with detailed step-by-step solutions
Enter Your Data
Statistical Summary
Data Distribution
Step-by-Step Calculation
Input Data
Your dataset contains 10 values:
Calculate the Mean (Average)
The mean is the sum of all values divided by the number of values.
Mean = (Σx) / N = (24 + 17 + 19 + 22 + 18 + 21 + 20 + 23 + 16 + 25) / 10 = 205 / 10 = 20.5
Calculate Deviations from Mean
For each value, subtract the mean and square the result:
Calculate Variance
For population variance, divide the sum of squared differences by the number of values (N). For sample variance, divide by N-1.
Sum of squared differences = 12.25 + 12.25 + 2.25 + 2.25 + 6.25 + 0.25 + 0.25 + 6.25 + 20.25 + 20.25 = 82.5
Population Variance = Σ(x – μ)² / N = 82.5 / 10 = 8.25
Calculate Standard Deviation
Standard deviation is the square root of the variance.
Population Standard Deviation = √(Variance) = √8.25 ≈ 2.87
Standard Deviation Calculator
Title: Standard Deviation Calculator Find SD & Variance
Description: Calculate standard deviation, mean, and variance from a dataset. Use our Standard Deviation Calculator for statistics and research.
Standard Deviation Calculator
Quickly find the standard deviation, variance, and mean of your data using our powerful Standard Deviation Calculator. Essential for data analysts and researchers.
- Handles grouped and ungrouped data.
- Shows calculation steps.
- Great for statistics students and professionals.
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Standard Deviation Calculator: - Calculate population & sample standard deviation, variance, and other statistical measures with detailed step-by-step solutions
- Enter Your Data
- Data Set (comma or space separated):Data Type:PopulationSampleDecimal Places: 2 3 4 5 Calculate StatisticsReset
- Statistical Summary
- Data Points
- 10
- Mean (Average)
- 20.50
- Standard Deviation
- 3.03
- (Population)
- Variance
- 9.20
- Median
- 20.50
- Mode
- –
- Range
- 9.00
- Sum
- 205.00
- Data Distribution
- Step-by-Step Calculation
- 1
- Input Data
- Your dataset contains 10 values:
- 24
- 17
- 19
- 22
- 18
- 21
- 20
- 23
- 16
- 25
- 2
- Calculate the Mean (Average)
- The mean is the sum of all values divided by the number of values.
- Mean = (Σx) / N = (24 + 17 + 19 + 22 + 18 + 21 + 20 + 23 + 16 + 25) / 10 = 205 / 10 = 20.5
- 3
- Calculate Deviations from Mean
- For each value, subtract the mean and square the result:
- (24-20.5)² = 12.25
- (17-20.5)² = 12.25
- (19-20.5)² = 2.25
- (22-20.5)² = 2.25
- (18-20.5)² = 6.25
- (21-20.5)² = 0.25
- (20-20.5)² = 0.25
- (23-20.5)² = 6.25
- (16-20.5)² = 20.25
- (25-20.5)² = 20.25
- 4
- Calculate Variance
- For population variance, divide the sum of squared differences by the number of values (N). For sample variance, divide by N-1.
- Sum of squared differences = 12.25 + 12.25 + 2.25 + 2.25 + 6.25 + 0.25 + 0.25 + 6.25 + 20.25 + 20.25 = 82.5
- Population Variance = Σ(x – μ)² / N = 82.5 / 10 = 8.25
- 5
- Calculate Standard Deviation
- Standard deviation is the square root of the variance.
- Population Standard Deviation = √(Variance) = √8.25 ≈ 2.87
- Sample Standard Deviation:
It is worth noting that there exist many different equations for calculating sample standard deviation since, unlike sample mean, sample standard deviation does not have any single estimator that is unbiased, efficient, and has a maximum likelihood. The equation provided below is the “corrected sample standard deviation.”
As such, the “corrected sample standard deviation” is the most commonly used estimator for population standard deviation, and is generally referred to as simply the “sample standard deviation.” It is a much better estimate than its uncorrected version, but still has a significant bias for small sample sizes (N<10). - 2025 Standard Deviation Calculator | Statistical Analysis Tool
