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Learning outcomes

  • define frequency distribution
  • build a frequency table for categorical data
  • compute relative frequency and percentage
  • interpret the most common category correctly

What is a frequency distribution?

  • A frequency distribution shows how often each category occurs.
  • It is one of the simplest ways to summarize categorical data.
Example raw data:
  • CSE, ECE, CSE, ME, CSE, ECE, CE, CSE
Frequency table:
BranchFrequency
CSE4
ECE2
ME1
CE1

Why frequency distributions matter

  • They reduce messy raw data into a usable summary.
  • They help identify:
    • most common category
    • least common category
    • distribution pattern

Relative frequency

  • Relative frequency tells what proportion of observations fall in each category.
Formula:
  • relative frequency = category frequency / total frequency
Using the example above:
  • total = 8
  • for CSE, relative frequency = 4/8 = 0.5

Percentage distribution

  • Percentage gives relative frequency in percent form.
Formula:
  • percentage = relative frequency x 100
Example:
  • CSE = 0.5 x 100 = 50%

Complete table format

CategoryFrequencyRelative FrequencyPercentage
CSE40.5050%
ECE20.2525%
ME10.12512.5%
CE10.12512.5%

Things to check in a correct table

  • all categories are included
  • category labels are clear
  • frequencies add to total
  • relative frequencies add to 1
  • percentages add to 100% apart from rounding differences

Exam hints and traps

  • Frequency is count, not percentage.
  • Relative frequency is not written as raw count.
  • Percentages may sum to 99.9% or 100.1% due to rounding.
  • The “most frequent” category is the mode.

Quick practice

Raw responses:
  • A, B, A, C, A, B, D, B, A, C
  1. Construct a frequency table.
  2. Find the relative frequency of B.
  3. Which category is the mode?

Answer key

    • A = 4, B = 3, C = 2, D = 1
  1. 3/10 = 0.3
  2. A