How to use this frequency table calculator
Paste raw values above and press Calculate. The calculator counts each distinct value, then builds the full table: frequency, relative frequency (percentage) and cumulative frequency: the three columns every textbook asks for.
From a pile of numbers to a table with a story
Raw data is mute. Twelve quiz results in a list (5, 7, 8, 7, 9, 5, 8, 7, 6, 8, 9, 7) tell you almost nothing until they are counted. The frequency table is the first act of organisation in statistics: it turns the pile into a distribution you can see, chart and argue about.
Counting the twelve scores: 5 appears twice, 6 once, 7 four times, 8 three times, 9 twice. Relative frequencies follow (7 gives 33.3%), and the cumulative column climbs 2, 3, 7, 10, 12. Read cumulatively, the table now answers questions the raw list could not: "how many scored 7 or below?". Seven students, visible at a glance.
Grouped frequency tables
When values span a wide range (heights, incomes), counting one row per value produces a useless phone book. Then values are grouped into class intervals (150–159, 160–169) and counted per class. The craft is in the width: too wide hides the shape, too narrow fragments it. Five to ten classes suits most classroom datasets; the class width formula (range ÷ number of classes, rounded up) lives in this site's guides.
Frequently asked questions
What are the three columns of a frequency table?
Frequency (the count), relative frequency (count ÷ total, often a percentage), and cumulative frequency (the running total up to and including that value).
What is relative frequency?
The proportion of observations in a category: frequency divided by the total count. All relative frequencies sum to 1 (or 100%).
When should data be grouped into classes?
When there are many distinct values across a wide range. Grouping into 5–10 intervals reveals the distribution's shape without a row per value.