Unit 1.3 – Representing a Categorical Variable with Tables

Why Tables?
**Tables** are a clear way to organize, display, and analyze data for categorical variables. They allow us to quickly see counts, percentages, and comparisons.

🗂️ Types of Tables for Categorical Data

  • Frequency Table: Shows number of cases in each category
  • Relative Frequency Table: Shows proportion or percentage in each category
  • Two-way (Contingency) Table: Shows how two categorical variables interact
Frequency Table Example
Favorite Color Count
Red 12
Blue 8
Green 10
Relative Frequency Table Example
Favorite Color Percent
Red 40%
Blue 27%
Green 33%

📒 Anatomy of a Good Table

  • Clear title describes what the table shows
  • All categories are mutually exclusive (no overlaps)
  • Includes all possible categories (even if zero!)
  • Totals (count = n, percentages = 100%) always shown

🔑 Key Formula: Relative Frequency

\[ \text{Relative Frequency (proportion)} = \frac{\text{Count in Category}}{\text{Total Count}} \]
\[ \text{Percentage in Category} = \frac{\text{Count in Category}}{\text{Total Count}} \times 100\% \]

💡 Study Tips & Tricks

  • Double-check row/column labels match the question and data
  • Add “Other” category if needed for completeness
  • Use bar charts to visualize frequency table results
  • Report both counts and percentages for max clarity
  • For two-way tables, always state which variable is the row and which is column

❌ Common Mistakes

  • Not including every category (totals will be wrong!)
  • Mixing up percent and proportions
  • Leaving out totals (always show overall n or 100%)
  • Rounding percentages so they don’t add to 100%
  • Putting quantitative data (like scores) into a frequency table—should be grouped first
Summary:
Unit 1.3 covers how to represent a categorical variable with well-organized and correct tables: frequency tables, relative frequency tables, and two-way tables. Always show totals, be clear and organized, and know how to turn counts into proportions and percents!