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]]>Ratio scale has order and equally distanced values between units and at the same time has an absolute zero as well. It can quantify the difference between each value and ratios can also be calculated. Though, unlike interval scale, this scale does not have negative numbers because of absolute zero. To know whether a variable can be measured on the ratio scale one should see that whether it meets all the requirements for the interval scale if it does and it has an absolute zero then it can be measured on the ratio scale.

- A ratio scale has a rational zero point where the value of the variable has no value. For example, weight and height can be measured on ratio scale because they have a real zero value. On the other hand, the temperature cannot be measured on ratio scale because a zero degree centigrade temperature does not mean that there is no heat or cold. Most of the scientific variables like height, weight, age, density, strength, time, volume, speed can be measured on a ratio scale.
- A rational zero is necessary to measure the ratio between two values of a variable, in the absence of a real zero there is no ratio. In the absence of a zero, does it make sense to say that a student who got 100 marks in mathematics has got double as compare to the one who got 50?
- A scientific variable cannot be measured precisely on nominal, ordinal or interval variable, in the absence of a ratio scale, scientific variables cannot be measured.

A wide range of all descriptive and inferential statistics can be applied on the ratio scale. All statistical analysis including mean, median, mode, variance, standard deviation, and the range can be calculated on a ratio scale. In addition, statistical tests like t-test, f-test, correlation, chi-square etc can also be calculated on ratio scale variable.

For detailed overview of the measurement scales read Types of Measurement Scales in Research

- Gideon Vigderhous,
*The Level of Measurement and Permissible Statistical Analysis in Social Research,*Pacific Sociological Review, Vol. 20, No. 1, 1977, pp. 61-72. - https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3963323/
- Campbell MJ, Machin D, Wiley J.
*Medical Statistics: A Commonsense Approach,*Vol. 2. London: Wiley; 1993.

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]]>- This scale has constant equal distances between each successive values.
- This scale has wide scope due to its characteristic that it can categorize the data in equal intervals.
- Mean and standard deviation can be applied to data measured using this scale. The range can also be calculated to obtain the data dispersion.

- This scale has all the characteristics of a complete measuring scale except that it does not have an absolute zero.

Selection of the right statistical technique and data analysis depends heavily on the variables to be studied and the measurement scales used in the research. Therefore, the selection of right measuring scale is crucial to the success of the research. Data that has been measured using this scale can be treated by one of the several statistical techniques including mean, standard deviation, regression, correlation, range, analysis of variance etc. Studentized range and coefficient of variation cannot be calculated because ratios have no meanings in this scale.

- Campbell MJ, Machin D, Wiley J.
*Medical Statistics: A Commonsense Approach.*Vol. 2. London: Wiley; 1993. - Stevens SS. Bobbs-Merrill,
*On the Theory of Scales of Measurement.*College Division; 1946. - Marateb H. Reza, et al,
*Manipulating measurement scales in medical statistical analysis and data mining: A review of methodologies.*Journal of Research in Medical Sciences; 2014 Jan; 19(1): 47–56.

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]]>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.

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.

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.

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.

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