The data are not linearly distributed unlike in the case of Fig. 9, indicating that the distribution cannot be explained only by the effect of normal heating.
But often marketing, production and distribution cannot be done by the business-school book.
This is why a probability sample is needed; without a probability sample, the sampling distribution cannot be determined and an interval estimate of a parameter cannot be constructed.
Hence, tail of the severity distribution cannot be modeled precisely.
Given the exigencies of the natural order, this distribution cannot be secured within this order.
Concretely, the travel time distribution cannot be well fitted by Normal distribution in most cases.
Moreover, information about wear distribution cannot be obtained on the basis of weight monitoring.
In the interfering condition the pressure distribution cannot be predicted accurately.
Thus, the null hypotheses (that is, the data has normal distribution) cannot be rejected.
However, as some studies do not report their parameter values, a representative distribution cannot be derived.
As in practice, the saturation distribution cannot be directly observed, tracer experiments are performed to characterize a fracture.
