Paste numbers from a spreadsheet or type them in, and instantly see the shape of your data with a histogram, mean and standard deviation lines, a normal curve and a box plot.
| Within | Your data | Normal (68-95-99.7) |
|---|
| Bin | Count | % |
|---|
Runs entirely in your browser. Nothing is uploaded to any server.
Spot skew, multiple peaks and gaps that averages hide.
The box plot flags values beyond 1.5 × IQR.
Compare your data with the 68-95-99.7 rule and a normal curve.
A histogram groups values into equal-width bins and shows how many fall in each one. The red line marks the mean, and the dashed lines mark one and two sample standard deviations either side of it. The orange curve is a normal distribution with the same mean and standard deviation, scaled to the histogram.
Quartiles use linear interpolation between sorted values, the same method as Excel's QUARTILE.INC. Skewness and excess kurtosis use the sample-adjusted formulas. Values near 0 for both suggest a roughly normal shape; positive skew means a longer right tail.
k = ⌈log₂ n + 1⌉ bins, good for small, roughly normal data.
Bin width 2 × IQR / ∛n, robust to outliers.
Box from Q1 to Q3, red median, whiskers to the last non-outlier.
Use the sample standard deviation when your data is a sample from a larger group, and the population value when it is the entire group.
Values below Q1 − 1.5 × IQR or above Q3 + 1.5 × IQR, which is Tukey's rule used in box plots.
For normally distributed data about 68% of values lie within one standard deviation of the mean, 95% within two and 99.7% within three.
No. Commas are treated as separators between numbers, so remove thousands separators first.
No. Everything is calculated in your browser.
More free tools from My Panda Toolbox.