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:Data Science by Emmanuel Schanzer, Nancy Pfenning, Emma Youndtsmith, Jennifer Poole, Shriram Krishnamurthi, Joe Politz, Ben Lerner, Flannery Denny, and Dorai Sitaram with help from Eric Allatta and Joy Straub
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.