Yes.
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There are several statistical measures of correlation: some require only a nominal scale, that is, data classified according to two criteria; others require an ordinal scale, which is the ability to determine whether one measurement is bigger or smaller than another; others require an interval scale, which allows you to determine the difference in values but not the ratio between them. [A good example of the latter is temperature measured in any scale other than Kelvin: the difference between 10 degrees C and 15 degrees C is 5 C degrees, but 15 C is not 1.5 times as warm as 10 C.]The contingency coefficient, which is suitable for nominal data, has a chi-squared distribution.The Spearman rank correlation, requiring ordinal data, has its own distribution for small data sets but as the number of units increases to n, the distribution approaches Student's t-distribution with n-2 degrees of freedom.The Kendall rank correlation coefficient can be used in identical situations and gives the same measure of significance. However, the Kendall coefficient can also be used to test partial correlation - whether the correlation between two variables is "genuine" or whether it arises because both variables are actually correlated to a third variable.The Pearson's product moment correlation coefficient (PMCC) is the most powerful but requires measurement on an interval scale as well as an underlying bivariate Normal distribution.The significance levels of these correlation measures are tabulated for testing.A simple "rule of thumb" for testing the significance of PMCC is that values below -0.7 or above 0.7 are highly significant. Values in the ranges (-0.7, -0.3) and (0.3, 0.7) are moderate, and values between -0.3 and +0.3 are not significant.
1728 is a pure number. Without units it has no meaning in volumetric measurements.
You can say that the correlation is positive if and only if the slope is positive. The correlation is zero if and only if the slope is zero. And the correlation is negative if and only if the slope is negative. On the other hand, slope does change when your measurement units change, while correlation does not change. (For example, the correlation between height in inches and weight in pounds will be the same as the correlation between height in centimeters and weight in kilograms, as long as both sets of measurements were taken on the same observations.)
Ideal mechanical advantage is a numerical ratio. It's a naked number without a unit.
The fraction is4/(the weight of the whole thing, in pounds) . The fraction is a naked number, without units.