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Statistics I · Week 2 — Categorical data
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Statistics I · Week 2 — Categorical data
1021 words
5 min read
2026-08-16
Reading compass
Now · Week map
Week 2 — categorical data
Quiz 2 scope: Weeks 1–8 per IITM May 2026 foundation courses. Source baseline: IITM BS admissions important-dates calendar · May 2026 cycle. Times on assessments are operational conventions — verify hall ticket.
Week map
Categories → counts → relative frequency → bar/pie chart choice
Classify → Represent → Execute → Trap-check
- Recognize: Ask: How compute relative frequency?
- Procedure: Tally each category. Total n is sum of counts. Relative freq = count/n.
- Variations / traps: Watch for: Percents not summing to 100 due to rounding.
Formula chain (compressed)
frequency table → relative freq = count/n → bar/pie for categories.
- Frequency —
count per category— raw tallies - Relative frequency —
count / total— proportions sum to 1 - Mode —
most frequent category— categorical centre - Bar chart —
height = count or %— compare categories - Missing category —
include "other" or NA— complete sample space
Open interactive formula desk · Week 2 tab.
Deep study
Statistics I · Week 2 — Categorical data
Once variables are categories, analysis is counting and comparing shares — tables and charts, not means.
Week map
Categories → frequency table → relative frequency → percent → bar chart → pie chart → complements → rounding totals.
Frequency notation
- Frequency f → count in category → 23 students chose tea.
- Relative frequency → f/n → proportion of whole → 0.23 if n=100.
- Percent → relative × 100 → 23%.
- Complement → all categories not A → if A is 30%, complement is 70%.
Constraint: relative frequencies sum to 1 (percents sum to 100%) except rounding drift.
Mini-table: colors Red 40, Blue 35, Green 25, n=100.
- Rel freq: 0.40, 0.35, 0.25
- Percents: 40%, 35%, 25%
Charts
Bar chart
- Categories on axis (nominal or ordinal).
- Bar height = count or percent.
- Good for compare across categories.
Pie chart
- Wedges show part-whole.
- Works for few categories; weak for many thin slices.
- Angles proportional to relative frequency.
Trap: pie for unrelated totals not forming one meaningful whole.
Pattern families
Easy — Build frequency table
- Tally categories from raw list.
- Compute n as sum of counts.
- Relative freq = count/n.
Medium — Chart choice and read
- Pick bar vs pie from question goal.
- Read missing count from percent and n: count = percent/100 × n.
- Compare two categories via difference in counts or percents.
Hard — Rounding and complements
- Percents sum to 99% or 101% due to rounding — know largest category still identifiable often.
- Given two category percents, find third when three categories total 100%.
- Two-way categorical preview: row percent vs overall percent (setup for week 4).
Worked mini-examples
Example 1 — Relative frequency.
120 voters: A 54, B 36, C 30.
n=120. Rel: 0.45, 0.30, 0.25.
Example 2 — Percent to count.
n=250, 16% chose option D → count = 0.16 × 250 = 40.
Example 3 — Complement.
40% walked → 60% did not walk (single binary split).
Example 4 — Missing category.
Three flavors: chocolate 45%, vanilla 30%, strawberry ? → strawberry 25%.
Example 5 — Bar vs pie.
Six transport modes with similar counts → bar chart clearer. Two outcome yes/no → pie or bar both OK.
Traps
- Confusing frequency with relative frequency.
- Pie chart with dozens of categories.
- Percents not summing to 100 — rounding, not always error.
- Bar chart ordered as if ordinal when nominal — order arbitrary unless by count.
- Using pie when categories are not parts of one group total.
Diagnostic (try yourself)
-
Raw:
[R,R,B,G,R,B,G,G,R]— build frequency table and n. -
n=80, counts A=32, B=20, C=28. Find relative frequencies and percents.
-
In a survey, 35% preferred online and 45% preferred hybrid. The only other option is in-person. What percent chose in-person?
-
n=200, 12.5% chose “other”. How many cases?
-
When would a bar chart be better than a pie chart for the same categorical data? One sentence.
ChatGPT prep archive
Archived import for extra depth — complements the notes above, not official IITM material.
Core concepts
- Frequency: count per category.
- Relative frequency: proportion or percent of total; sums to 1 (or 100%).
- Bar chart: categories on axis; heights show counts or percents.
- Pie chart: wedges show parts of whole—meaningful for few categories.
Notation & vocabulary
| Term | Formula |
|---|---|
| rel freq | count / n |
| percent | rel freq × 100 |
| complement cat | all others combined |
Pattern families
Easy — Frequency table
Tally each category. Total n is sum of counts. Relative freq = count/n.
Medium — Choose chart
Bar for compare categories; pie only for part-whole with moderate category count. Avoid pie with many thin slices.
Hard — Missing category
Given percents summing to <100, infer missing share. Or find count from percent and n.
Drill these on the pattern atlas — filter to week 2.
Traps
- Percents not summing to 100 due to rounding.
- Bar chart with ordered nominal when order arbitrary.
- Pie chart for unrelated categories not one whole.
- Confusing frequency with relative frequency.
Retrieval prompts
- How compute relative frequency?
- When bar vs pie?
- What must pie wedges sum to?
Practice loop
- Read Deep study (if present) or core concepts once.
- Recite the formula chain without looking.
- Open one easy pattern on the interactive atlas for week 2.
- Attempt without solutions; mark studied after an honest try.
- Say one trap aloud before closing the tab.