Referenced from lesson Introduction to Computational Data Science
For each piece of data below, circle whether it is Categorical or Quantitative data.
1 |
Hair color |
categorical quantitative |
2 |
Age |
categorical quantitative |
3 |
ZIP Code |
categorical quantitative |
4 |
Year |
categorical quantitative |
5 |
Height |
categorical quantitative |
6 |
Sex |
categorical quantitative |
7 |
Street Name |
categorical quantitative |
For each question, circle whether it will be answered by Categorical or Quantitative data.
8 |
We’d like to find out the average price of cars in a lot. |
categorical quantitative |
9 |
We’d like to find out the most popular color for cars. |
categorical quantitative |
10 |
We’d like to find out which puppy is the youngest. |
categorical quantitative |
11 |
We’d like to find out which cats have been fixed. |
categorical quantitative |
12 |
We want to know which people have a ZIP code of 02907. |
categorical quantitative |
13 |
We’d like to sort a list of phone numbers by area code. |
categorical quantitative |
These materials were developed partly through support of the National Science Foundation,
(awards 1042210, 1535276, 1648684, and 1738598). 
Bootstrap:Integrated Oklahoma by Jen Poole
is licensed under a
Creative Commons 4.0 Unported License.
Based on a work at www.BootstrapWorld.org.
Permissions beyond the scope of this license may be available by contacting
schanzer@BootstrapWorld.org.