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]. http://en.wikibooks.org/wiki/Statistics/Different_Types_of_Data/Quantitative_and_Qualitative_Data http://www.cimt.plymouth.ac.uk/projects/mepres/book7/bk7i11/bk7_11i1.htm Click to access 03a_continuous_descriptive.slides.pdf Which scales of measurement are associated with quantitative data?The measurement scales are used to measure qualitative and quantitative data. With nominal and ordinal scale being used to measure qualitative data while interval and ratio scales are used to measure quantitative data.
What are the four 4 levels of scale measurement in quantitative research?Nominal, ordinal, interval, and ratio scales explained. There are four levels of measurement (or scales) to be aware of: nominal, ordinal, interval, and ratio.
Is a 1/10 scale quantitative data?Data from Likert scales and continuous (e.g. 1-10) rating scales are quantitative. These scales assume equal intervals between points.
Which scales of measurement are qualitative?Qualitative variable (also called categorical variable) shows the quality or properties of the data. It is represented by a name, a symbol, or a number code. These scales are mutually exclusive (no overlap) and none of them have any numerical significance. It is two types: nominal and ordinal.
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