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Scales/levels of measurement
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Quantitative Methods in Language Studies
Terms in this set (4)
Nominal
The lowest level of data (least precise)
There are no differences in magnitude between values, one is just as good as any other
Examples: first languages, gender, nationality, days of the week
Numerically represented as frequencies, e.g.,
In the total sample of 120 test takers, 84 were female (70%) and 36 were male (30%).
This data type is sometimes also called "categorical" or "discrete"
Ordinal
Ranked, relative
There is a difference in magnitude but we don't know how large it is
Examples: Likert scale ratings, rankings, rater judgments
Numerical representation: frequencies, e.g.,65% of respondents agreed that the test was easy, 25% disagreed, and 10% were neutral.
Interval
Things based on the same underlying continuum
Each interval is equal in units apart - The differences in magnitude between the levels are assumed to be the same
Examples: test scores, age, length of residence, number of mistakes in a dictation
Numerical representation: mean & standard deviation
Interval data is the highest level of data and allows the most computations.
Ratio
Absolute zero.
The differences in magnitude between the levels are assumed to be the same
Examples: test scores, age, length of residence, number of mistakes in a dictation
Numerical representation: mean & standard deviation
Ratio data is theoretically even more detailed, but in practice there is no real difference between interval and ratio
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