To develop ideas quickly and build an intuition regarding supply and demand, we have a simple and completely hypothetical dataset of height, weight, and race of a few random samples obtained from a survey. Let's have a look at the dataset:
|
Height (inches) |
Weight (lbs) |
Race (Asian/African/Caucasian) |
|
72 |
180 |
Asian |
|
66 |
150 |
Asian |
|
70 |
190 |
African |
|
75 |
210 |
Caucasian |
|
64 |
150 |
Asian |
|
77 |
220 |
African |
|
70 |
200 |
Caucasian |
|
65 |
150 |
African |
Let's examine the individual fields:
- Height in inches and weight in lbs are continuous data types because they can take on any values, such as 65, 65.123, and 65.3456667.
- Race, on the other hand, would be an example of a categorical data type, because there are a finite number of possible values that can go in the field. In this example...
