Median Calculator

Find the median of a dataset instantly. Also calculates mean, mode, quartiles (Q1/Q2/Q3), IQR, outliers, and distribution shape from comma-separated numbers.

Median
Mean (Average)
Mode
Count (n)
Extended More scenarios, charts & detailed breakdown
Median
Mean
Range
Sorted Data
Professional Full parameters & maximum detail

Central Tendency

Median
Mean
Standard Deviation

Distribution Analysis

Skewness
Outliers (IQR × 1.5)
Distribution Shape

Data Preview

Sorted Data

How to Use This Calculator

  1. Enter your numbers as comma-separated values in the input field (e.g., 3, 7, 1, 9, 4).
  2. Click Calculate to see the median, mean, mode, and count.
  3. Use the Quartiles tab to find Q1, Q2, Q3, and IQR.
  4. Use Five Number Summary for the full min-Q1-median-Q3-max profile.
  5. Use the Professional tab for outlier detection, skewness indicator, and standard deviation.

Formula

Median (odd n): Middle value of sorted data

Median (even n): (value[n/2−1] + value[n/2]) / 2

IQR = Q3 − Q1 • Outlier bounds: Q1 − 1.5×IQR and Q3 + 1.5×IQR

Example

Example: Dataset: 3, 7, 1, 9, 4. Sorted: 1, 3, 4, 7, 9. n=5 (odd). Median = 4. Mean = (1+3+4+7+9)/5 = 4.8. Mode = none (all unique).

Frequently Asked Questions

  • The median is the middle value of a sorted dataset. If there are an even number of values, the median is the average of the two middle values. It is less affected by outliers than the mean.
  • The mean (average) adds all values and divides by count. The median is the middle value. In skewed datasets, the median better represents the "typical" value. For example, in income data, the median income is more informative than the mean income which is pulled up by billionaires.
  • The Interquartile Range (IQR = Q3 − Q1) measures the spread of the middle 50% of data. Values more than 1.5 × IQR below Q1 or above Q3 are typically classified as outliers.
  • The five number summary consists of: Minimum, Q1 (25th percentile), Median (50th percentile), Q3 (75th percentile), and Maximum. It gives a complete picture of the data distribution.
  • Use the median when data is skewed, has outliers, or is ordinal. Use the mean when data is roughly symmetric and normally distributed. The median is always preferred for income, home prices, and response times.

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