Categorical data sorts things into groups, such as eye color. Quantitative data measures an amount, such as height. If averaging the values would be meaningless, the data is categorical. Categorical data suits bar charts; quantitative data suits dot plots, histograms and box plots.
Step 1: Let's Learn
Read it, or press Listen and follow the words.
Numbers can still be categorical
Jersey numbers are digits, yet the average jersey number tells you nothing. Postcodes, phone numbers, ID codes: labels that look numeric. Ask whether the average would mean anything.
Sorting a list
Shoe size: quantitative, an amount. Favorite subject: categorical. Number of siblings: quantitative, a count. Bus route number: categorical, a label. Temperature: quantitative.
The gap matters
Bar chart bars stand apart because the categories are separate: nothing lies between "blue" and "green". Histogram bars touch because the numbers run continuously: 165 cm sits between 160 and 170.
What to look for
Describe shape, center and spread, and mention any outlier. Shape: symmetric, skewed, or with two peaks. Centre: where the middle sits. Spread: how far the values reach. Those four together describe a distribution.
Reading a histogram
Bars at 150–155: 2, 155–160: 6, 160–165: 12, 165–170: 11, 170–175: 7, 175–180: 2. Roughly symmetric, centered near 165 cm, spread from 150 to 180, no outliers. Four facts, one sentence.
Why the choice matters
The wrong display hides the story. A bar chart of heights loses the shape; a histogram of eye colors invents an order the colors never had. The graph should match what the data can say.
Step 2: Try It Yourself
Tap and try it out.
Classify each and name a display: favorite subject, minutes of homework, bus route number, number of pets
- Answerfavorite subject: an average subject is meaningless, categoricala bar chart, bars apart
Step 0 of 3
Apple
Banana
Cherry
Cherry has the most. It has 5 more than Banana.
Step 3: In Real Life
A school report
Favorite subjects are categories: a bar chart. Test scores are numbers: a histogram. A newspaper that puts categories on a histogram is misleading its readers before saying a word.
Step 4: Watch an Example
One step at a time.
Watch Amara Choose a Display
Amara has the heights of 40 students and wants to show the distribution.
- Step 1
She checks the type first: heights are amounts, so the data is quantitative. A bar chart is therefore wrong.
Step 5: Your Turn
Practice makes it stick.
The Survey
Problem 1 of 2
Eye color is which kind of data?
The Jerseys
Problem 2 of 2
Jersey numbers on a team are which kind?
Name the Data
1 of 8
Height in centimeters.
2 of 8
Favorite sport.
3 of 8
Number of siblings.
4 of 8
Postcode.
5 of 8
Do histogram bars touch?
6 of 8
How many features describe a distribution: shape, center, spread and outliers?
7 of 8
Sort each variable by its type.
Tap something to move it.
- Empty
- Empty
8 of 8
Temperature in degrees.
Step 6: Quick Check
Show what you know.
Question 1 of 2
Hair color is which kind of data?
Question 2 of 2
Why do histogram bars touch while bar chart bars do not?
What You Learned
- Categorical data sorts; quantitative data measures.
- If averaging the values is meaningless, the data is categorical, however numeric it looks.
- Bar charts for categories, bars apart; histograms for amounts, bars touching.
- Describe a distribution by shape, center, spread and outliers.