Most count variables are ratio measurements, for example, the number of clients in past six months. Why? Because you can have zero clients and because it is meaningful to say that "...we had twice as many clients in the past six months as we did in the previous six months."[1]

 

Examples of business world ratio-level measurements include production cycle type, work measurement time, passenger miles, number of trucks old, complaints per 10,000 fliers, and number of employees.

 

With ratio-level data, no b factor is required in converting units from one measurement to another, that is, y = ax: Feet = 3 x yards

 

Nominal- and ordinal-level data, often derived from imprecise measurements such as demographic surveys, are called non-metric data and are sometimes referred to as qualitative data.

 

Interval- and ratio-level data are usually gathered by precise instruments called metric data and are sometimes referred to as quantitative data.[2]

 

Raw data (or ungrouped data) is data that have not been summarized in any way.

Grouped data is data that have been organized into a frequency distribution.