An empirical distribution describes the observed distribution of a raw dataset without assumptions about its mathematical form.
Even if you figure your way past such slips of the pen, you might as well not have bothered: when the raw material is heroic assumptions, the (pretty trivial) net outcomes are guesstimates at best.
Following this assumption, the raw pixel values in luminance channel are used as the color propagation domain [3, 16].
Second, the use of raw scores satisfied regression model assumptions, whereas the use of T-scores, even with transformations, strongly violated these assumptions.
The Department of Labor's Bureau of Labor Statistics reports this assumption -- yes, an assumption based on a raw data.
They might be put down as Negroes who feel the humiliation of their race so deeply that they will not even join in the orthodox movements for its emancipation, because these are, to their raw sensitiveness, tainted with the assumption that Negroes have to behave like good children to win a favorable report from the white people.
At the outset, we start with the assumption that the raw frames may be distorted, and so, it is also reasonable to assume that the reference image, the average over the frames, may be imperfect.
The conceptual model was reduced into a logical model with the assumption that the raw input and output files are made available (in a repository similar to iBIOMES or MoDEL) and that the model would be used to index the data rather than providing a complete view of the results (e.g. calculation output, structures defined in each MD trajectory frame).
Second, means were compared between Babson's and the raw data based on the assumption that the data was not skewed, and therefore the 50th percentiles were equal to the mean.
It provides a lot of the raw material that feeds their negative assumptions about politicians.
