Some measure of the undisputed general importance of quantification in the natural sciences can be gleaned from the following comments:
"these are mere facts, but they are quantitative facts and the basis of science."[1]
It seems to be held as universally true that "the foundation of quantification is measurement."[2]
There is little doubt that "quantification provided a basis for the objectivity of science."[3]
In ancient times, "musicians and artists ... rejected quantification, but merchants, by definition, quantified their affairs, in order to survive, made them visible on parchment and paper."[4]
Any reasonable "comparison between Aristotle and Galileo shows clearly that there can be no unique lawfulness discovered without detailed quantification."[5]
Even today, "universities use imperfect instruments called 'exams' to indirectly quantify something they call knowledge."[6]
In some instances in the natural sciences a seemingly intangible concept may be quantified by creating a scale—for example, a pain scale in medical research, or a discomfort scale at the intersection of meteorology and human physiology such as the heat index measuring the combined perceived effect of heat and humidity, or the wind chill factor measuring the combined perceived effects of cold and wind.
Frequently in the use of regression, the presence or absence of a trait is quantified by employing a dummy variable, which takes on the value 1 in the presence of the trait or the value 0 in the absence of the trait.
Quantitative linguistics is an area of linguistics that relies on quantification. For example,[7] indices of grammaticalizationofmorphemes, such as phonological shortness, dependence on surroundings, and fusion with the verb, have been developed and found to be significantly correlated across languages with stage of evolution of function of the morpheme.
The ease of quantification is one of the features used to distinguish hard and soft sciences from each other. Scientists often consider hard sciences to be more scientific or rigorous, but this is disputed by social scientists who maintain that appropriate rigor includes the qualitative evaluation of the broader contexts of qualitative data. In some social sciences such as sociology, quantitative data are difficult to obtain, either because laboratory conditions are not present or because the issues involved are conceptual but not directly quantifiable. Thus in these cases qualitative methods are preferred. [citation needed]
