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Mean, Median, Mode & Range Calculator

Enter any dataset and instantly get mean, median, mode, range, IQR, quartiles, outliers, and a full frequency table. Up to 200 values supported.

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Mean, Median, Mode & Range Guide

Guide

Mean, Median, Mode & Range Calculator – Free Statistics Tool

Mean, median, mode, and range are the four fundamental measures of central tendency and spread in descriptive statistics. Whether you are a GCSE student in the UK calculating the average of a frequency table, a US middle school student working on data sets, or a data analyst summarising a distribution, these four measures give you a quick and clear picture of your data. Our free calculator computes all four instantly, along with interquartile range (IQR), quartiles, outlier detection, and a complete frequency table.

The Mean (Arithmetic Average)

The mean is calculated by adding all the values together and dividing by the count:

Mean = Sum of all values / Number of values

xΜ„ = (x₁ + xβ‚‚ + ... + xβ‚™) / n

Example: The exam scores 55, 62, 70, 78, 85 have mean = (55+62+70+78+85)/5 = 350/5 = 70.

The mean is sensitive to outliers. A single very high or very low value can pull the mean significantly. This is why income data is often reported using median rather than mean β€” a small number of very high earners pull the mean salary well above what most people earn.

Mean in Real Life β€” Salary Data

UK: The UK Office for National Statistics (ONS) reports that the median annual salary for full-time employees was approximately Β£34,900 in 2024, while the mean was notably higher at around Β£39,000 β€” illustrating the effect of high earners on the mean.

US: The US Census Bureau similarly shows median household income being consistently lower than mean household income due to the right-skewed distribution of incomes β€” a classic example of mean vs median in practice.

The Median (Middle Value)

The median is the middle value when data is sorted in order. It divides the dataset in half β€” 50% of values are above and 50% below.

  • For an odd number of values: the median is the middle value
  • For an even number of values: the median is the average of the two middle values

Example (odd): Sorted data: 3, 7, 9, 12, 15. Median = 9 (position 3 of 5).

Example (even): Sorted data: 3, 7, 9, 12. Median = (7+9)/2 = 8.

The median is resistant to outliers β€” adding a value of 1,000,000 to the dataset above would barely change the median but would dramatically increase the mean.

The Mode (Most Frequent Value)

The mode is the value (or values) that appear most frequently in a dataset. A dataset can have:

  • No mode β€” if all values appear exactly once
  • One mode (unimodal) β€” one value appears more than any other
  • Two modes (bimodal) β€” two values tie for highest frequency
  • Multiple modes (multimodal) β€” three or more values share highest frequency

Example: In the dataset {2, 3, 3, 5, 7, 7, 7, 9}, the mode is 7 (appears 3 times).

Mode is the only measure of central tendency applicable to categorical (non-numeric) data. "The most common hair colour in the class is brown" β€” that is a mode.

The Range

Range = Maximum value βˆ’ Minimum value. It is the simplest measure of spread:

Example: {4, 8, 15, 16, 23, 42} β†’ Range = 42 βˆ’ 4 = 38.

Range is highly sensitive to outliers. Remove the 42 and the range drops to 19. The range gives no information about how the middle values are distributed.

Interquartile Range (IQR) and Quartiles

The IQR measures the spread of the middle 50% of data, making it much more robust to outliers than the range:

IQR = Q3 βˆ’ Q1

Quartiles divide sorted data into four equal parts:

  • Q1 (Lower Quartile) β€” 25th percentile, the median of the lower half
  • Q2 (Median) β€” 50th percentile
  • Q3 (Upper Quartile) β€” 75th percentile, the median of the upper half

The box plot (box-and-whisker diagram) displays Q1, Q2, Q3, and the extent of the whiskers β€” a visual summary of the five-number summary (minimum, Q1, median, Q3, maximum).

Outlier Detection β€” The 1.5 Γ— IQR Rule

A commonly used rule for identifying outliers:

  • Lower fence = Q1 βˆ’ 1.5 Γ— IQR
  • Upper fence = Q3 + 1.5 Γ— IQR
  • Any value below the lower fence or above the upper fence is flagged as a potential outlier

This is the rule used by Tukey's box plots and is the standard in most statistics courses and software.

When to Use Mean vs Median vs Mode

MeasureBest Used WhenSensitive to Outliers?
MeanData is roughly symmetric with no extreme outliers; most statistical calculationsYes β€” highly
MedianData is skewed; there are outliers; reporting income, house prices, salariesNo β€” resistant
ModeCategorical data; finding the most common response; bimodal distributionsNo
RangeQuick overview of spread; very small datasetsYes β€” extremely
IQRRobust spread measure; box plots; outlier detectionNo β€” resistant

Skewed Distributions and the Mean-Median Relationship

In a perfectly symmetric distribution, mean = median = mode. In skewed distributions:

  • Right-skewed (positive skew): Mean > Median > Mode. Example: income data, house prices.
  • Left-skewed (negative skew): Mean < Median < Mode. Example: age at retirement.

The direction in which the tail points is the direction of the skew. A right-skewed distribution has a long right tail.

UK GCSE Statistics

In England, Wales, and Northern Ireland, mean, median, mode, and range are core GCSE Mathematics topics, appearing in Foundation and Higher tier papers. Students are expected to calculate these measures from raw data and from frequency tables. GCSE Statistics goes further to include quartiles, IQR, box plots, and comparing distributions. All major exam boards (AQA, Edexcel, OCR) test these topics frequently.

US Middle School and AP Statistics

In the US, measures of central tendency are introduced in Grade 6 Math under Common Core State Standards (6.SP standards). AP Statistics covers all descriptive statistics including quartiles, IQR, outlier rules, and comparison of distributions in Unit 1. The AP exam regularly asks students to compare two distributions using shape, centre (mean/median), and spread (SD/IQR).

House Prices β€” A Real-World Example

UK: According to the UK Land Registry, the mean house price in England in 2024 was significantly higher than the median, pulled up by expensive London properties. The Office for National Statistics recommends the median as a more representative measure of typical house prices.

US: The US Census Bureau's American Housing Survey similarly reports both median and mean home values. The median is the standard reporting figure for housing market health.

Frequently Asked Questions

What is the difference between mean, median, and mode?

Mean = sum of all values Γ· count (the arithmetic average). Median = the middle value when data is sorted. Mode = the most frequently occurring value. All three are measures of the "typical" value in a dataset, but they respond differently to outliers and skewed data.

When should I use median instead of mean?

Use median when data is skewed or contains outliers. Income, salaries, house prices, and healthcare costs are typically reported using median rather than mean because a small number of very high values would make the mean unrepresentative of the typical person's experience.

Can a dataset have more than one mode?

Yes. If two values appear the same number of times (and more than any other value), the dataset is bimodal and has two modes. If three or more values share the highest frequency, the dataset is multimodal. If all values appear exactly once, there is no mode.

What is the IQR and why is it useful?

IQR (Interquartile Range) = Q3 βˆ’ Q1. It measures the spread of the middle 50% of data. Unlike range, it is not affected by outliers, making it a robust measure of spread. It is used in box plots and to define the Tukey fence for outlier detection (1.5 Γ— IQR below Q1 or above Q3).

How do I find the median of an even-numbered dataset?

Sort the data in ascending order. If n is even, the median is the average of the two middle values: (value at position n/2 + value at position n/2 + 1) / 2. For {3, 7, 9, 12}: median = (7+9)/2 = 8.

What is an outlier in statistics?

An outlier is a value that is unusually far from the rest of the data. The Tukey rule defines outliers as values below Q1 βˆ’ 1.5Γ—IQR or above Q3 + 1.5Γ—IQR. Outliers may be genuine extreme values or data entry errors. Their effect should be considered before deciding whether to include them in analysis.

Is mean always greater than median?

No. In a symmetric distribution they are equal. In a right-skewed distribution, mean > median. In a left-skewed distribution, mean < median. This is why income data (right-skewed) has mean salary always higher than median salary.

Are mean, median, and mode covered at GCSE in the UK?

Yes. Mean, median, mode, and range are core GCSE Mathematics topics at both Foundation and Higher tier. GCSE Statistics also covers quartiles, IQR, and box plots. All major UK exam boards (AQA, Edexcel, OCR) test these topics in every exam series.

⚠️ Disclaimer

Important

Results are for educational and informational purposes. Statistical calculations depend on correct data entry. Different software may use slightly different quartile calculation methods.

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