Categorical data sorts things into groups, such as eye colour. Quantitative data measures an amount, such as height.
Step 1: Let's Learn
Read it, or press Listen and follow the words.
A quick test
If averaging the values would be meaningless, the data is categorical. The average of "blue" and "green" is nothing at all.
Numbers can still be categorical
Jersey numbers are digits, yet the average jersey number tells you nothing. Labels can look numeric.
Matching the display
Categorical data suits bar charts. Quantitative data suits dot plots, histograms and box plots.
The gap matters
Bar chart bars stand apart because the categories are separate. Histogram bars touch because the numbers run continuously.
What to look for
Describe shape, centre and spread, and mention any outlier. Those four together describe a distribution.
Categorical or quantitative
Categorical data record which group something belongs to; quantitative data record how much. You can average heights and not eye colours, so the type decides which summaries and graphs are even meaningful.
Discrete and continuous
Discrete quantitative data come in separate values — number of children. Continuous data can take any value in a range — height. The distinction decides whether a bar chart or a histogram is appropriate.
Matching display to data
Bar charts and pie charts for categories; dot plots, histograms and box plots for quantitative data. Using a pie chart for quantities, or a histogram for categories, misrepresents the data structurally.
Numbers are not always quantitative
Postal codes and jersey numbers are numerals labelling categories. Averaging them produces a number with no meaning. Checking whether arithmetic on the values makes sense is the real test of data type.
Step 2: Try It Yourself
Tap and try it out.
Apple
Banana
Cherry
Cherry has the most. It has 5 more than Banana.
Step 3: 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.
Step 4: Your Turn
Practice makes it stick.
The Survey
Problem 1 of 2
Eye colour is which kind of data? Enter 1 for categorical, 2 for quantitative.
The Jerseys
Problem 2 of 2
Jersey numbers on a team are which kind? 1 categorical, 2 quantitative.
Name the Data
1 of 8
Height in centimetres. 1 categorical, 2 quantitative.
2 of 8
Favourite sport. 1 or 2?
3 of 8
Number of siblings. 1 or 2?
4 of 8
Postcode. 1 or 2?
5 of 8
Do histogram bars touch? 1 for yes, 0 for no.
6 of 8
How many features describe a distribution: shape, centre, 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. 1 or 2?
Step 5: Quick Check
Show what you know.
Question 1 of 2
Hair colour is which kind of data? 1 categorical, 2 quantitative.
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.
- Describe a distribution by shape, centre, spread and outliers.