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There are basically four measurement scales in statistics that are used to categorize the variables under study. These four measurement scales include; nominal, ordinal, interval and ratio scales. In physical science, the measurement needs to be very accurate and precise but in social science, the measurement cannot be as accurate and it is a lot more subjective. The measurement scale needs to be very accurate to get the most valid and reliable results.
Measurement scales:
Nominal or classificatory scale
The nominal or classificatory scale is the most simple scale that is used in statistics and research. This scale only identifies the variables under study into unique values. This scale does not provide numerical values to the variables. The variables are only compared on the basis of some unique characteristic descriptively. Kumar R. (2000) defines nominal scale as the classifications of individuals, objects or responses based on common or shared property or characteristics. These people, objects or responses are divided into a number of subgroups in such a way that each member of the sub-groups has a common characteristic. This scale is most commonly used to categorize ‘gender’ or other simple variables, such variables do not have numerical values. Gender can be either male or female, but you cannot assign some numerical values to gender like 100 percent male etc.
Ordinal or ranking scale
The ordinal scale has the properties of the nominal scale, but it is a little more advanced than nominal scale. It categorizes values assigned to the variables on the basis of their magnitude. Some values related to the variables will be ‘smaller’ while other will be ‘larger’ or in other cases, some values will be ‘greater’ than the other values which will be ‘lesser’. The values are arranged either in ascending or descending order, so there is an ordered relationship between the values in the scale. This scale, however, does not categorize the values on the scale in fixed intervals.
Interval scale
The interval scale has the properties of the ordinal and nominal scale, which means that it assigns unique values to the each value under study and it also categorizes the values in ascending or descending order. The unique property of the interval scale that makes it different from the previous two scales is that it also categorize the values in equal intervals. In this scale, any of the two values on the scale has an equal interval. Temperature can be categorized using the interval scale, for example, values in centigrade can be spaced at equal interval using this scale. It also happens that in this scale the values have a starting point and an ending point. The space between 0-degree centigrade to 100-degree centigrade is always equally spaced.
Ratio scale
This scale has all the properties of the previous scales plus one of its own properties that it has a fixed zero point, and below that point, no value exists. Every value can be measured from an absolute zero point or starting point, due to this property this scale is called as an absolute scale and for most empirical and mathematical operations this scale is used. Weight and height are the best examples of variables that can be measured on the ratio scale, they have an absolute zero point and no value exists below that. Temperature, which can be measured on the interval scale, cannot be measured on the ratio scale because the temperature can be below zero so there are no absolute zero points.