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/ Home / LernStats / Scale Quality / Scale Quality
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LernStats
(Chapter 1 - Page 2 / 5)
Scale Quality
- Nominal scale. The nominal scale assumes only the equality or inequality of attributes (e.g. gender) or the possibility of classifiable distinctions (e.g. occupation, natural language, hair colour, course of studies).
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- Ordinal scale (Rank scale). The ordinal scale uses less-than and greater-than relations within the data. Data can be ordered. For that reason values in an ordinal scale are also called ranks.
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- Interval (metric) Interval scales are scales where the difference between two values can be defined as greater, equal or less than the difference between two other values. Differences (and sums) of values can be compared. Adding and subtracting data values only makes sense with interval-scaled data. A interval scale has three arbitrary elements: a starting (or zero-) point, a size of scale and direction in which the units are chosen, starting at the starting point.
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- Ratio (metric) scale . Besides an arbitrarily defined scale the ratio scale has a natural zero or starting point (just like the absolute zero in the Kelvin temperature - scale).
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