Categorical Variable vs Quantitative Variable
Both terms below come up in the same part of the course, and students mix them up. Here is each one defined on its own, side by side, so you can see where they part company.
Categorical variable
Variables and data types
A categorical variable records which group or category an individual belongs to, rather than a numerical measurement.
The values of a categorical variable are labels, so arithmetic like averaging them has no meaning. For example, eye color with values blue, brown, and green is categorical, as are yes or no answers. You summarize categorical data with counts and proportions, and display it with bar graphs. If 30 of 120 people have blue eyes, the proportion is , or 25 percent.
Quantitative variable
Variables and data types
A quantitative variable records a numerical measurement or count for which arithmetic such as averaging is meaningful.
Quantitative values are numbers that measure how much or how many, so you can add and average them. For example, height in centimeters, age in years, and number of siblings are all quantitative. You summarize this kind of data with measures like the mean (x-bar) and standard deviation, and display it with dotplots or histograms. Averaging the values 4, 5, and 9 gives .