One of the key aspects of design is understanding the classification of data which enables doing exploratory analysis, choosing chart types and layout decisions.
Data classifications are below
1. Qualitative
2. Quantitative
1. Qualitative:
Textual:
It’s unstructured stream of data
Example:
- ” Are you alright ?”
- ” Temperature now is 40 degree celcius”
Nominal:
It’s categorical data offering means of distinguishing, labelling and organising values . Its used to label values without any quantitative values.
Example :
- Gender
- Hair colour of kids
Ordinal :
It’s categorical data with characteristics of order
Example :
- Academic Grades ( 1- Excellent , 2- Very Good , 3- Good , 4- Average, 5- Poor)
- Survey Response ( 1- Unhappy , 2 – Neutral, 3 – Happy)
– Education level ( High Graduate, Undergraduate,Graduate)
2. Quantitative – Discrete , Continuous – Interval, Ratio
Discrete :
It’s data associated with all classifying variables with no inbetween states.
Example :
- Head or tail of coin
- Size of dresses
Continuous:
It can hold value of in- between state
Interval :
Numeric measurement defined on a scale
Example :
- Weather forecast ( 5°C , 10°C )
Ratio :
Numeric measurement that has properties of difference and scale
Example :
- Age of employee
- Forecasted amount of rainfall
Hope this article will be helpful for you.