Advanced Summary Statistics Tool

Compute central tendency, spread, shape, and percentile insights. Review clean tables and interpretive metrics instantly. Export findings for reporting, teaching, audits, and smarter decisions.

Summary Statistics Calculator

Paste values separated by commas, spaces, semicolons, or new lines.

Use decimals or negative numbers when needed.
Included outputs
  • Center, spread, shape, and range metrics
  • Quartiles, percentile, fences, and outliers
  • Geometric, harmonic, and trimmed means
  • CSV and PDF exports for result sharing

Example Data Table

Use this sample to test the tool and compare your own outputs.

Observation Value Observation Value
112724
215827
315930
4181030
5211133
6211236

Formula Used

Mean: x̄ = Σx / n

Median: middle ordered value, or average of two middle values.

Range: max − min

Interquartile range: IQR = Q3 − Q1

Percentile: linear interpolation on the ordered dataset.

Trimmed mean: remove the selected count from both tails, then average the remaining values.

Sample variance: s² = Σ(x − x̄)² / (n − 1)

Population variance: σ² = Σ(x − μ)² / n

Standard deviation: square root of variance

Coefficient of variation: CV = standard deviation / |mean| × 100

Outlier fences: Q1 − k×IQR and Q3 + k×IQR

Mean interval: mean ± z × standard error, using the selected confidence level.

How to Use This Calculator

  1. Paste or type numeric observations into the dataset box.
  2. Choose whether your numbers represent a sample or a full population.
  3. Set the percentile, trim percentage, confidence level, and outlier factor.
  4. Pick the number of displayed decimal places.
  5. Click Calculate Statistics to show the results above the form.
  6. Use the export buttons to download a CSV or PDF report.

FAQs

1. What kind of values can I enter?

You can enter integers, decimals, negatives, and repeated values. Separate them with commas, spaces, semicolons, or line breaks. Non-numeric entries trigger a validation error.

2. When should I choose sample instead of population?

Choose sample when your dataset represents only part of a larger group. Choose population when the values include every member of the group you want to describe.

3. How is the percentile calculated here?

The tool sorts the data, finds the requested percentile position, and uses linear interpolation when the position falls between two observations. This gives a smooth percentile estimate.

4. Why might geometric mean show unavailable?

Geometric mean requires every value to be positive. If the dataset contains zero or any negative number, that measure is not mathematically valid and is hidden.

5. Why might harmonic mean show unavailable?

Harmonic mean cannot be computed when any value equals zero. Division by zero breaks the formula, so the tool marks that result as unavailable.

6. What does skewness tell me?

Skewness shows asymmetry. Positive values suggest a longer right tail. Negative values suggest a longer left tail. Values near zero usually indicate a more balanced shape.

7. How are outliers flagged?

The calculator uses lower and upper fences built from quartiles and the selected IQR factor. Any value outside those fences appears in the outlier result line.

8. Does the confidence interval use a z value?

Yes. The mean interval uses a normal-approximation z score with the selected confidence level and the standard error. It is useful for quick screening and reporting.

Related Calculators

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Important Note: All the Calculators listed in this site are for educational purpose only and we do not guarentee the accuracy of results. Please do consult with other sources as well.