Sentence examples for Numerical discrepancy from inspiring English sources

The numerical discrepancy does not become evident in the laminar flow simulation but in the turbulent flow simulation.

"Full answers have already been provided and have not been challenged," the former minister said, attributing a numerical discrepancy to a 2004 change of accounting rules for registering defence expenditure.

The reason for the numerical discrepancy could be because Yahoo is not calculating earnouts or share portions of acquisitions (Tumblr if you recall was an almost all-cash deal).

Although this finding possibly might explain the numerical discrepancy between the rather small number of genes and the complexity of the signaling network in complex organisms such as humans [37], it raises questions about how a single hub protein can interact with so many different partners [38].

The numerical discrepancy between all records (3996) and those containing quantitative data (43) points to the possibility of increasing the latter via data curation.

The key point is that prevalences have little bearing to the CIR, which comes to show that, beyond any numerical discrepancy, the interpretation of PR in terms of a CIR also implies a conceptual misunderstanding.

One approach is to eliminate numerical discrepancies.

For such applications it may be difficult to distinguish between results that are correct but differ because of numerical discrepancies, and results that are erroneous.

Arguing that the Pentateuch must have been a postexilic forgery rather than a faithful contemporary account of Jewish life, he also maintained that the numerical discrepancies found in Genesis warranted doubts concerning the historical accuracy of the Bible.

The numerical discrepancies between the reports are partially due to methodology differences, like whether a company is in Internet or software, or whether an international firm gets only its US investing activity counted.

A web-based, automated data platform (Doctor Evidence, Santa Monica, CA) further cross-calculated the data to identify any numerical discrepancies (i.e., mismatches of sub-data to main population data, data reported in percentiles conflicting with unit data and vice versa).