Scales of Measurement in a nutshell refers to various measures of the variables researchers use in their research, variables in the research are fall in one of 4 scales of measurement that will be discussed in this article. They hold prime importance in the Data Analysis, as the type of measure determine the kind of test to be used for data analysis. thus without understanding the concept of Scales of Measurement one could not have solid grasp of data analysis techniques.

Scales of Measurement in a nutshell refers to various measures of the variables researchers use in their research, variables in the research are fall in one of 4 scales of measurement that will be discussed in this article. They hold prime importance in the Data Analysis, as the type of measure determine the kind of test to be used for data analysis. thus without understanding the concept of Scales of Measurement one could not have solid grasp of data analysis techniques. Different items of the questionnaire are treated as variables, for instance Age is one variable,

The Question "**Do you Enjoy your work**" is another varibale, Gender is another varibale or Occupation could be another varibale, All items are treated as separate variables in the Questionnaire. All variables would fall in one of the 4 scales of measurement identified below

- Nominal
- Ordinal
- Interval
- Ratio

The process of measurement involves assigning numbers to observations according to rules. The way that the numbers are assigned determines the scale of measurement. Each scale of measurement represents a particular property or set of properties of the abstract number system. The mathematical properties of the numbers we are going to analyze are important because they determine statistical techniques to be used.

The properties of the abstract number system that are relevant to scales of measurement are identity, magnitude, equal interval, and absolute/true zero.

### Identity

Identification refers to assignment of a number to respondents response, and these number are just for the sake of identification and the numbers itself cannot be used in mathematical operations thus numbers assigned are just to convery a particular meaning. for instance Assigning 1 to Male, 2 to Female, Here we could have assigned 1 to Female and 2 to Male, and that would have made no difference. Variable having Identity property where number are assigned to values of the variable for the purpose of identification are measured on Nominal Scale.

### Magnitude

Moving one step ahead, a variable could have Identification and Magnitude as well, meaning that numbers have an inherent order from smaller to large. for instance Postion in Class, Level of Education or Rank in Organisation. Here the values of the variable have numbers for identification but also the values have some order for example the position variable has number 1, 2 and 3 for identification but all these 3 position have an order as well because the difference of Marks between 1st and 2nd could be 30 whereas difference between 2nd and 3rd could be of 50 marks, meaning on the continuum the difference is not the same. Variables having Identity and Magnitude are measured on Ordinal Scale.

### Equal Intervals

It Means that difference between numbers anywhere on the scale are the same, for instance take the variable Position, now it is measured on Ordinal Scale but not on Interval Scale because the distance between 1st and 2nd position may well not be the same as 2nd and 3rd, or 3rd and 4th. Here the distance refers to the Marks obtained by the position holders. In Most business researches Likert Scale variables are taken as having equal interval. or any variable where the difference between two units is the same as difference between any of the following following or previous two units for instance the difference between 4 and 5 is the same as the difference between 76 and 77 i-e 1. Variables with Equal Intervals, Magnitude and Identification Properties are measured on Interval Scale.

### Absolute/true zero

Means that the zero as a response represents the absence of the property being measured (e.g., no money, no behavior, none correct) but temperature on 0 is not absolute zero as it still has some effect and we cannot say no temperature. Thus putting a variable or user response in Nominal, Ordinal Interval or Ratio scale depends on the above mentioned properties it shows.

Next we would discuss the 4 scales of Measurements, Namely Nominal, Ordinal, Interval and Ratio in greater detail. If you have any queries please use the feedback link on top of the page and we would make sure we answer your queries.

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