Sentence examples for a high variance of from inspiring English sources

The phrase "a high variance of" is correct and usable in written English.
It can be used when discussing statistical data, variability, or differences in a particular context, such as research or analysis.
Example: "The study revealed a high variance of results among the participants, indicating differing levels of understanding."
Alternatives: "a large variation in" or "a significant disparity of".

Exact(16)

We recruit subjects from economics and non-economics majors to have a high variance of preferences and abilities.

The disadvantage is that the classifier has a high variance of the classification results.

As it was previously stated, a high variance of the OLLA offset can degrade its performance.

High loading value for Mn, strongly correlated with a high variance of Ca along PC2 axis indicate the influence these elements on within-group cohesion (see Figure 2).

While individual decision trees suffer from a high variance of estimates the averaging across the bootstrap sample leads to a significant variance reduction [90, 91].

However, in GLM, the interaction term showed no significance which may be caused by a high variance of SUVmax differences in combination with a small sample size.

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Similar(44)

Incorporating spatial clustering of smaller-scale faults around large faults results in a higher variance of bulk permeability.

Figure 6 shows that the proposed method has a higher variance of the capacity on a per-user basis than LF-OSDMA and the extended LF-OSDMA.

The main difference in these two distributions is a higher variance of (Delta f) for Pc3n _L) sample in comparison with that for Pc3n _D) sample.

A larger δ leads, in general, to a higher variance of the reliability as can be seen in Figure10, but the influence of the metric on R is rather limited.

However, if one group of applicants has a higher variance of unobserved variables, then job applicants from this group are more likely to pass the threshold due to the longer tails of the distribution of unobserved variables.

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