# Descriptive Statistics Calculator: All Key Metrics in One Place
Whether you are a student, researcher, or data analyst, the Descriptive Statistics Calculator gives you an instant, complete statistical summary of any numerical dataset. Paste your data and get 15 statistics calculated simultaneously — no spreadsheet software required.# Statistics Calculated
| Statistic | Description |
|---|---|
| Count (N) | Total number of values in the dataset. |
| Mean | The arithmetic average of all values. |
| Median | The middle value when data is sorted. Robust to outliers. |
| Mode | The most frequently occurring value(s). |
| Std Dev | Sample standard deviation (divides by N-1). |
| Variance | Square of the sample standard deviation. |
| Min / Max | Smallest and largest values in the dataset. |
| Range | Difference between the maximum and minimum values. |
| Q1 / Q3 | First and third quartiles (25th and 75th percentiles). |
| IQR | Interquartile range: Q3 minus Q1. Measures central spread. |
| Skewness | Asymmetry of the distribution relative to its mean. |
| Kurtosis | Excess kurtosis: tail weight relative to a normal distribution. |
When to Use Median Instead of Mean
If your data has significant outliers (e.g., income data, housing prices), the median is a more representative measure of central tendency than the mean, which is pulled toward extreme values.# Interpreting the Histogram
The frequency histogram shows how your values are distributed across equal-width bins, calculated automatically using Sturges' rule (k = 1 + log₂N). A symmetric bell shape suggests a normal distribution. Skewed shapes confirm the skewness value shown in the results.# Quick Reference Glossary
- IQR
- Interquartile Range. The spread of the middle 50% of your data. Used to identify outliers.
- Skewness
- Measures distribution asymmetry. Positive = right tail longer. Negative = left tail longer.
- Excess Kurtosis
- Tail heaviness compared to a normal distribution. 0 is normal; positive means heavier tails.
- Bessel's Correction
- Dividing by N-1 instead of N when computing sample variance to reduce bias in estimation.