The phrase "testing factors" is correct and usable in written English.
It can be used when discussing variables or elements that are being evaluated or examined in a particular context, such as experiments or assessments.
Example: "In our study, we identified several testing factors that could influence the results of the experiment."
Alternatives: "evaluating variables" or "assessment elements."
The orientation, the number and the central angle of the biomimetic structure were taken as the testing factors.
For instance, Zwick (2010) believed that test administrations based on computer might elicit several new and important sources of DIF that do not exist in paper-and-pencil testing, factors such as anxiety, differential computer familiarity, and facility.
Testing factors influencing determination of soil water transmission properties by an infiltrometer method helps better interpretation of the collected data and allows the development of appropriate sampling strategies for the intended use of the data.
The experiments involved testing factors that comprised the visual angle, size and shape of glyph arrays, frequency of temporal modulation, phase shift of each pattern, and number of stimuli.
In this study, a two-layer feed-forward neural network was constructed and applied to determine a mapping associating mix design and testing factors of cement nano silica (NS rice husk ash ternary blended concrete samples with their performance in conductance to the water absorption properties.
The relevant round robin test program provides valuable data generated during the experimental activity and statistical analysis thereof; then, based on the various testing approaches employed, the advantages/drawbacks of certain testing factors are summarized and critically assessed, reflecting the experience of involved institutions.
For validity testing, factor analysis and item analysis were conducted; and for reliability testing, internal consistency and test-retest reliability methods were used.
The multiple testing factor is the expected number of overlaps between the two subsets of the given sizes, given the two platforms P1 and P2.
Different orthogonal test factors and levels were set (Table 1).
The effect of all the tested factors is statistically significant.
Table 5 One sample test for individual factor's impact analysis One-sample test Factors Test value = 0 t Sig.
