📊 Statistics

11 calculators in this category.

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Paste your numbers to get the standard deviation, variance, mean, median, mode, quartiles and percentiles, with each step shown.

Find outliers, compare two variables with correlation and a least-squares regression line, and measure spread with the coefficient of variation.

Standard Deviation

Calculate the sample and population standard deviation, variance, mean, standard error and sum of squares from a list of numbers, with a step-by-step table.

Variance

Find the sample variance s² and population variance σ² of a data set, with the mean, standard deviation and a table of squared deviations.

Mean Median Mode

Find the mean (average), median, mode and range of a list of numbers, plus quartiles, the sorted data, a frequency chart and how each is worked out.

Coefficient of Variation

Calculate the coefficient of variation (relative standard deviation) of your data — SD ÷ mean × 100% — to compare variability between data sets.

Geometric Mean

Find the geometric mean of positive numbers, or the true average growth rate (CAGR-style) of percentages, compared with the arithmetic and harmonic means.

Harmonic Mean

Find the harmonic mean — the correct average for speeds over equal distances and other rates — with optional weights and a comparison with the arithmetic and geometric means.

IQR & Quartiles

Find Q1, the median, Q3 and the interquartile range of your data, with the five-number summary, outlier fences and the working shown.

Outlier Calculator

Find outliers in your data with Tukey’s 1.5 × IQR fences and the z-score method — mild and extreme outliers, fences and the data without them.

Percentile

Find any percentile of a data set (inclusive, exclusive and nearest-rank methods) and the percentile rank of a value, with a table of common percentiles.

Correlation

Calculate the Pearson correlation coefficient r, r², Spearman’s rank correlation, covariance and a significance test for two sets of paired data.

Linear Regression

Find the least-squares regression line y = bx + a, r², the standard error, slope significance, predictions and residuals, with a chart of the fitted line.

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