Statistics Calculators

Analyse your data with confidence using our Statistics calculators. Compute sample and population standard deviation, variance, mean, median, mode, and range from any data set, with deviation tables and distribution charts that make every step auditable. Perform linear regression analysis to find the line of best fit, calculate slope, intercept, Pearson correlation coefficient (r), and coefficient of determination (R²). Whether you are a student working through an introductory statistics course, a quality control engineer monitoring process variation, a researcher summarising measurements, or a financial analyst quantifying volatility, these tools deliver instant, accurate results with the formulas shown in full. All calculations run entirely in your browser – no data is stored or shared.

Linear Regression Calculator

Standard Deviation Calculator

How to Use Statistics Calculators

Browse the calculators in this category to find the tool that matches your task. Each calculator accepts your inputs and displays results instantly. Use the Normal mode for standard calculations and switch to Advanced mode for additional parameters and finer control over your results.

Why Choose Our Statistics Calculators

Our calculators combine accuracy, speed, and privacy in a clean, responsive interface. Every tool uses industry-standard formulas and runs entirely in your browser. All calculations run locally in your browser with no data storage required.

Regular updates ensure alignment with the latest standards and guidelines. Dark mode, keyboard shortcuts, and mobile-friendly design make the tools comfortable to use anywhere. Bookmark your favourites for one-click access to fast, reliable calculations.

Frequently Asked Questions

Enter your values, choose Sample or Population, and the calculator does the rest: it finds the mean, squares each deviation from it, averages them (dividing by n − 1 for a sample or N for a population), and takes the square root. A deviation table shows every intermediate step so you can audit the arithmetic.

The sample formula divides the sum of squared deviations by n − 1 (Bessel's correction), while the population formula divides by N. Use the sample version when your data is a subset of a larger group and the population version only when you have every member. For the same numbers, the sample result is always equal to or larger than the population result.

Linear regression finds the best-fit straight line through paired X and Y data, showing how the response variable changes with the predictor. It outputs the slope, intercept, Pearson correlation r, and R², and can predict Y at new X values. Common uses include forecasting, calibration curves, and trend analysis.

Variance σ² measures the average squared deviation from the mean. Standard deviation σ is its square root and is in the same units as your data, making it the interpretable form. About 68% of normally distributed data falls within ±1σ of the mean, 95% within ±2σ.

For bell-shaped data, roughly 68% of values lie within one standard deviation of the mean, 95% within two, and 99.7% within three. It converts any mean-plus-sigma pair into immediate probability statements. The rule only holds for approximately normal distributions.

A sample standard deviation needs at least two values; a regression line needs at least two distinct X values. For meaningful results, aim for five or more. Estimates become more precise as the square root of your sample size grows, so quadrupling your data halves the uncertainty of the mean.

Yes. Both tools accept any real numbers, positive, negative, whole, or decimal, in any order. Enter all values in a single consistent unit so the results stay interpretable.

R², the coefficient of determination, is the share of variance in Y explained by X. A value of 0.85 means 85% of the variability in the response is accounted for by the model. Controlled lab work often exceeds 0.95, while social science results of 0.30 to 0.50 can still be meaningful.

Use the median for skewed data or data with extreme outliers, such as incomes, house prices, or hospital stay lengths. A long tail drags the mean away from what a typical member experiences. The standard deviation calculator reports both, and a gap between them is the classic signature of skew.

The coefficient of variation (CV) expresses the standard deviation as a percentage of the mean. Because it is unit-free, it lets you compare variability across different scales: 2% CV on a production line is tight control, while 40% CV on ecological field data is unremarkable. It is undefined when the mean is zero.

No. All calculations run entirely in your browser. Your values are never sent to a server, stored, or shared. Close the tab and your data is gone.

A confidence interval is calculated as estimate ± margin of error. For a population mean with known σ, use CI = x̄ ± z* × σ/√n, where z* is 1.96 for a 95% confidence level. The standard error σ/√n appears in the standard deviation calculator's results.