Measurement can be defined as a process of associating numbers to observations obtained in a research study. The variables associated with a study are classified into two basic categories: Quantitative/ Numeric Qualitative / Categorical

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Incidentally, only quantitative variables can be measured with the help of standard counting devices and qualitative variables can only be observed , there is no standard device or instrument to measure them. For example, in case of human beings, there are certain Quantitative( physical) characteristics like height, weight etc and there are certain qualitative ( abstract) characteristics like beauty, attitude, creativity etc.

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Like human beings, a business organization has also some Physical characteristics like employees, sales, offices etc. Being physical in nature these are easily measurable. However, there are certain abstract characteristics like reputation of the employees, image of the entity, motivation, work culture, commitment, trust, customer’s perception, feelings of customers. All these are extremely important because they help the company to stay afloat and grow.

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Therefore characteristics have to be measured for their meaningful assessment . This can be done by assigning some numbers and forming scales.

Classification or Types of Measurement Scales:

Classification or Types of Measurement Scales All measurement scales can be classified into the following four categories: Nominal Ordinal Interval Ratio

Properties of Scales :

Properties of Scales Distinctive classification Order Equal distance Fixed origin

Distinctive classification( Nominal Data) :

Distinctive classification( Nominal Data) A measure that can be used to classify objects or their characteristics into distinctive classes /categories is said to have this property. For example: gender classifies the individuals into distinctive groups, males and females. The individuals may also be classified on the basis of their Occupation, like student, salaried, businessman etc. Similarly, the qualification of an individual could be used to classify individuals into various categories such as undergraduate, postgraduate, professional etc. Similarly, we can classify a person based on marital status like married, unmarried, widowed, divorced .

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Categorical data is qualitative or descriptive data, which can be made into numerical data if we code the various categories. For example if we record marital status as 1 . married 2. Unmarried 3 . widowed and 4. divorced. Nominal data are numerical data for namesake only, because they do not share any properties of the numbers we deal in ordinary mathematics. For instance we cannot write 4> 3 or 1<2.

Order ( Ordinal Data):

Order ( Ordinal Data) A measure is said to have an order if the objects or their characteristics can be arranged in a meaningful order. For example, marks of a student (Quantitative data) can be arranged in an ascending or descending order. As another example, a consumer may asked to rank four telecom service providers ( say A, B, C and D) on the basis of the connectivity.( Qualitative data)

Equal distance/Interval :

Equal distance/Interval If for a measure the difference between any two consecutive categories of a measured attribute are equal then the measure is said to have equal distance. For example, in temperature readings the difference between 40 0 C and 50 0 C is same as between 60 0 C and 70 0 C. Similarly the Time measurement also follow the same property.

Fixed Origin:

Fixed Origin A measurement scale is said to have a fixed origin if there is a meaningful zero or absence of the characteristics. Examples are income of an individual, sales of a company, Profit of a company. etc. Zero income signifies absence of income, Zero sales signifies absence of sales

Types of Scales :

Types of Scales Nominal Scale : This scale is used to divide the population into various subgroups/categories or classes. It do not satisfy the other three properties mentioned above. It is termed as ‘nominal’, as though one may represent the categories using numbers , the numbers are just for namesake, they do not carry any value or order or meaning. Example: If we put up a question like ‘which type of vehicle is used for going to office ? The answer could be bus, car, motor cycle, auto etc. Numerical value can be assigned to classify these categories like 1,2, 3, 4. Sometimes codes are used for classification like STD codes for cities, codes for various subjects in a university etc. The data collected through a nominal scale is known as a nominal data.

2. Ordinal Scale:

2. Ordinal Scale A qualitative scale with order is called an ordinal scale. This scale possesses first two of the four properties of the scale , i.e. the properties of distinctive classification as well as order or rank like 1 st , 2 nd , 3 rd etc. The ordinal scale places events in order, but there is no attempt to make the intervals of the scale equal. For example, if in a class of students , the highest mark is 95 , next is 85 and the next is 84, converting marks to ranks will lead to 1,2, and 3. Incidentally, it may be noted that the difference in the performance of the 1 st ranker and 2 nd ranker is not the same as the 2 nd ranker and 3 rd ranker. Thus, one can only conclude that 1 st ranker has performed better than 2 nd ranker and 2nd ranker better than 3rd ranker.

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The data obtained using ordinal scale is termed as ordinal data. Some examples are: ● Ratings of hotels, restaurants and movies. We can say 5 star hotel is better than a 4 star hotel, but we cannot say that a 4 star hotel is twice good as a 2 star hotel. ● Class of travel in a train or an aero plane. ● grades of students in a class.

3. Interval Scale :

3. Interval Scale A measurement scale whose successive values represent equal value of the characteristics that is being measured, and whose base value is not fixed, is called an interval scale. This is a quantitative scale of measure without a fixed or true zero. Some examples are temperature( Fahrenheit scale) , time, longitude, latitude etc.

4. Ratio Scale :

4. Ratio Scale Ratio scales are quantitative measures with fixed or true zero. Ratio scales has all four properties of scales that are described above. For example, a weighing scale is a ratio scale. Some other examples are height, price, sales, revenue, profit etc. In all these cases zero implies absence of that characteristic.

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