Stats Calculator
MathCompute count, sum, mean, median, mode, min, max, range, variance and standard deviation from a list of numbers for data analysis, reports and stats homework.
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About Stats Calculator
Descriptive statistics is the first step of data analysis — given a set of measurements or samples, you look at central tendency and dispersion before deciding how to model further. This tool computes eleven metrics at once: count, sum, mean, median, mode, min, max, range, variance, standard deviation and sum of squares. Enter numbers separated by commas or spaces. Everything runs locally in the browser, ideal for students checking homework, researchers scanning distributions and PMs reconciling report figures. For example, entering 2,4,4,4,5,5,7,9 yields mean 5, median 4.5, standard deviation about 2.2 and eight more metrics in one go.
How to Use
- Open the Stats Calculator tool
- Enter the values to calculate
- Adjust the output options as needed
- Click the Calculate button; results appear in real time
- Copy or export the result
Use Cases
- Homework check — Paste exercise data to verify hand-calculated mean, variance and stddev and locate step errors.
- Lab data scan — Quickly inspect the range and dispersion of measurements to judge instrument stability and outliers.
- Report reconciliation — Compare mean vs median from backend exports to spot skew and outlier inflation.
- Quality control — Track standard-deviation drift in production samples to catch process shifts early.
- Rating summary — Use mode and median on review scores to resist extreme ratings skewing the mean.
- A/B test quick scan — Compute mean and variance for both control and variant groups to gauge significance before running a full test.
- Performance benchmark — Paste latency measurements to get mean, stddev and range for comparing framework or query performance.
FAQ
Why does mode show "No mode"?
When every value occurs equally often there is statistically no mode, and the tool reports so; if several values tie for most frequent, all are listed.
Is variance population or sample?
This is population variance (divided by n), suited to describing the dataset itself; for inferential work use sample variance (n-1).
Are decimals and negatives supported?
Yes. Any valid number (decimal, negative, scientific notation) is parsed; non-numeric tokens are ignored.
Are quantiles included?
This release focuses on eleven core metrics; quantiles are not yet provided but may be added later.