A measured variable in a data can be classified among 4 measurement scale.
Nominal Scale: As name suggest this scale is related to different names of categories. This measurement scale is basically used to define non ordered levels or types of a categorical variable.These levels have no preference one over other.
Example: Gender, Vehicle-type, Blood Group etc.
Ordinal Scale: This scale has a set preference of one level or category over other, but it can not be put this measurement into any number, i.e. one level is different from other by what value. The ordered levels have a definite pattern.
Example: Grades, Travel Class, etc.
Interval Scale: In this scale every observed value can be expressed in terms of numbers. This is a big relief, as since now we were just talking of levels & orders. The scale have a property of equal interval, but no scope of a reference i.e. 'a true zero'. This means you can add or subtract but can't do multiplication or division.
Let's elaborate with an example. Consider a compressed air application, if air is having 4 bar g pressure, you can increase the pressure by 5 bar g to make it a 9 bar g pressure. This is a simple increment and no. adds up. But we can never say that an 8 bar g pressure is twice high pressure as compared to 4 bar g. So this scale has an additive property.
Also if we say that vacuum has a zero pressure, still we can measure it and will not say an absence of pressure as there are concept of negative pressure also.
Let's elaborate with an example. Consider a compressed air application, if air is having 4 bar g pressure, you can increase the pressure by 5 bar g to make it a 9 bar g pressure. This is a simple increment and no. adds up. But we can never say that an 8 bar g pressure is twice high pressure as compared to 4 bar g. So this scale has an additive property.
Also if we say that vacuum has a zero pressure, still we can measure it and will not say an absence of pressure as there are concept of negative pressure also.
Example: Pressure, Temperature etc.
Ratio Scale: This is a measurement which has equal interval as well as a reference of 'true zero'. This scale is placed at the top of measurement scale, as it possess all the properties of measurement. Best example for this weight scale, as it has a measurement of 0 lbs as true zero and we can't have negative weights.
Example: Height, weight.
Below is an example of all the scales in data collection process.
Example: Height, weight.
Below is an example of all the scales in data collection process.
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