There are four scales of measurement: Nominal, Ordinal, Interval, Ratio. Show These are considered under qualitative and quantitative data as under: Qualitative data:
In this scale, categories are nominated names (hence “nominal”). There is no inherent order between categories. Put simply, one cannot say that a particular category is superior/ better than another. Examples:
The various categories can be logically arranged in a meaningful order. However, the difference between the categories is not “meaningful”. Examples:
Quantitative data:
The values (not categories) can be ordered and have a meaningful difference, but doubling is not meaningful. This is because of the absence of an “absolute zero”. Example: The Celsius scale: The difference between 40 C and 50 C is the same as that between 20 C and 30 C (meaningful difference = equidistant). Besides, 50 C is hotter than 40 C (order). However, 20 C is not half as hot as 40 C and vice versa (doubling is not meaningful). Meaningful difference: In the Celsius scale, the difference between each unit is the same anywhere on the scale- the difference between 49 C and 50 C is the same as the difference between any two consecutive values on the scale ( 1 unit).[Thus, (2-1)= (23-22)= (40-39)=(99-98)= 1].
The values can be ordered, have a meaningful difference, and doubling is also meaningful. There is an “absolute zero”. Examples:
In addition, quantitative data may also be classified as being either Discrete or Continuous. Discrete: The values can be specific numbers only. Fractions are meaningless. In some situations, mathematical functions are not possible, too. Examples:
Continuous: Any numerical value (including fractions) is possible and meaningful. Examples:
Most of the numerical data we use is continuous. As you might have noticed by now, the Ratio scale often involves continuous data [Temperature is an exception, unless the Kelvin scale is being used]. What is a level of measurement where the data have order and rank?The ordinal level of measurement indicates an ordering of the measurements.
Is ranking ordinal or interval?Ordinal: Numbers that have an order like a runner's finishing place in a race, the rank of a sports team and the values you get from rating scales used in surveys or questionnaires like the Single Ease Question.
What level of measurement involves data that may be arranged in some order?Interval - data can be arranged in order, and we can determine meaningful amounts of differences between data.
What is the level of measurement of a data that is arranged in order but differences between data are not meaningful?Data at the ordinal level of measurement are quantitative or qualitative. They can be arranged in order (ranked), but differences between entries are not meaningful.
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