Statistics Calculator: Mean, Standard Deviation and Line of Best Fit
Mean, median, spread and range of a list of numbers, or a least-squares straight line through x and y pairs.
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Calculated from standard textbook formulas, with every step shown. The formulas are fixed, so the working does not need checking: what matters is the numbers you type in. Use these calculators only if you are competent to choose the inputs (loads, material strength, dimensions, supports) and check your units and assumptions. For learning and checking your own working: design and sign-off are for a qualified engineer. Drafting Central does not store the numbers you type.
How this calculator works
Paste a list of readings, one per line. The calculator gives the count, mean, median, the sample and population standard deviations, and the range. Use the sample standard deviation (divide by n minus 1) for a sample of readings, and the population one (divide by n) when you have every value.
If each line has two numbers (x and y), it also fits the best straight line by least squares and gives R squared. A value near 1 means the points lie close to a line, but it does not prove the relationship is a line: always plot the points.
Formulas used
- s = \sqrt{\frac{\sum (y_i - \bar y)^2}{n-1}}
- m = \frac{\sum (x_i - \bar x)(y_i - \bar y)}{\sum (x_i - \bar x)^2}
- c = \bar y - m\bar x
Worked example
With the default numbers in the calculator above:
- Count, mean: 5 values, mean 12.24
- Median: 12.2
- Sample standard deviation: 0.27019
- Population standard deviation: 0.24166
- Smallest, largest and range: 0.7
Change the numbers in the calculator to see the full working, every step, for your own case.
Common questions
Sample or population standard deviation?
Sample if your numbers are a sample of a larger set of readings (the usual case). Population if they are all of them.
What does R squared tell me?
How much of the scatter of y is explained by the straight line. 1 is a perfect line.
How many numbers can I enter?
Up to 500 lines.
Related calculators
Further reading: Montgomery and Runger, Applied Statistics and Probability for Engineers.
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