The interval to use for a bar graph with data ranging from 12 to 39 units would be six. Since the two given values are multiples of three, it is best to go with an interval of six (i.e., 0,6,12,18,24,30,36, 42).
Quantitative attributes are all measurable on interval scales, as any difference between the levels of an attribute can be multiplied by any real number to exceed or equal another difference.
The central tendency of a variable measured at the interval level can be represented by its mode, its median or its arithmetic mean. Statistical dispersion can be measured in most of the usual ways, which just involved differences or averaging, such as range, interquartile range and standard deviation. Since one cannot divide, one cannot define measures that require a ratio, such as studentised range or coefficient of variation. More subtly, while one can define moments about the origin, only central moments are useful, since the choice of origin is arbitrary and not meaningful. One can define standardised moments, since ratios of differences are meaningful but one cannot define coefficient of variation, since the mean is a moment about the origin, unlike the standard deviation, which is (the square root of) a central moment.
Quantitative attributes are all measurable on interval scales, as any difference between the levels of an attribute can be multiplied by any real number to exceed or equal another difference.
The central tendency of a variable measured at the interval level can be represented by its mode, its median or its arithmetic mean. Statistical dispersion can be measured in most of the usual ways, which just involved differences or averaging, such as range, interquartile range and standard deviation. Since one cannot divide, one cannot define measures that require a ratio, such as studentised range or coefficient of variation. More subtly, while one can define moments about the origin, only central moments are useful, since the choice of origin is arbitrary and not meaningful. One can define standardised moments, since ratios of differences are meaningful but one cannot define coefficient of variation, since the mean is a moment about the origin, unlike the standard deviation, which is (the square root of) a central moment.
