RANGE (STATISTICS)
In descriptive statistics, the 'range' is the length of the smallest interval which contains all the data. It is calculated by subtracting the smallest observations from the greatest and provides an indication of statistical dispersion.
It is measured in the same units as the data. Since it only depends on two of the observations, it is a poor and weak measure of dispersion except when the sample size is large.
For a population, the range is more than twice the standard deviation.
The range, in the sense of the difference between the highest and the lowest scores is also called the 'crude range'. When a new scale for measurement is developed, then a potential maximum or minimum will emanate from this scale. This is called the 'potential (crude) range'. Of course this range should not be chosen too small, in order to avoid a ceiling effect. When the measurement is obtained, the resulting smallest or greatest observation, will provide the 'observed (crude) range'.
The ''midrange'' point, i.e. the point halfway between the two extremes, is an indicator of the central tendency of the data. Again it is not particularly robust for small samples.
★ Interquartile range
★ Peirce's criterion
It is measured in the same units as the data. Since it only depends on two of the observations, it is a poor and weak measure of dispersion except when the sample size is large.
For a population, the range is more than twice the standard deviation.
The range, in the sense of the difference between the highest and the lowest scores is also called the 'crude range'. When a new scale for measurement is developed, then a potential maximum or minimum will emanate from this scale. This is called the 'potential (crude) range'. Of course this range should not be chosen too small, in order to avoid a ceiling effect. When the measurement is obtained, the resulting smallest or greatest observation, will provide the 'observed (crude) range'.
The ''midrange'' point, i.e. the point halfway between the two extremes, is an indicator of the central tendency of the data. Again it is not particularly robust for small samples.
| Contents |
| See also |
See also
★ Interquartile range
★ Peirce's criterion
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