MEASUREMENT AND SCALING TECHNIQUES

Presented by :Sem Shaikh

MEANING :

• 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:

a) Quantitative/ Numeric

b) Qualitative / Categorical

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.

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.

• 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

• All measurement scales can be classified into the following four categories:

(i) Nominal

(ii) Ordinal

(iii) Interval

(iv) Ratio

PROPERTIES OF SCALES

• Distinctive classification

• Order

• Equal distance

• Fixed origin

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.

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)

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)

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 400 C and 500 C is same as between 600 C and 700 C.

Similarly the Time measurement also follow the same

property.

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

1. 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 SCALEA 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 1st , 2nd, 3rd 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 1st ranker and

2nd ranker is not the same as the 2nd ranker and 3rd ranker.

Thus, one can only conclude that 1st ranker has performed better

than 2nd ranker and 2nd ranker better than 3rd ranker.

• 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

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

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.