Sentence examples for variance of word from inspiring English sources

Exact(2)

In other words, the community membership can explain part of the variance of word usage.

The variance of word counts is very close to the mean, which is expected from the Poisson distribution.

Similar(58)

Because the PFM is estimated as a difference between word counts in the test and control sets of sequences [Equations (e1) and (e2)], the variance of PFM elements is equal to the sum of variances of word counts in the test and control sequences.

In order to evaluate the polarity inversion that characterizes the MMN component at the mastoids locations [20], we performed an analysis of variance of condition (Word, non-word) and electrode (non re-referenced left mastoid and right mastoid locations).

Components extracted were named as follows: incremental theory of intelligence (ITI, with 31.7% variance), dislike of word problems (DLW, with 9.2%), arithmetic speed (AS, with 8.2%), entity theory of intelligence (ETI, with 6.6%), effort avoidance (EA, with 5.0%), and time persistence (TP, with 4.7%).

The exact nature of these long-lasting effects is yet unknown, but possibly parental educational attainment level influences the variance decomposition of word recognition ability in childhood, which then remains stable over time.

Yet, this study illustrates that variables like parental educational attainment level, which characterizes the childhood home-environment, may have long-lasting effects on the variance decomposition of word recognition ability.

Calculation of the expected value and variance of the word counts assumes that we know the background model that describes the sequence.

Additionally, the variance of individual word counts should be considered, since, for example, a high number of CAGCTG occurrences is more informative than a high count of self overlapping words such as AAAAAA where a Poly-A stretch of length 15 already gives 10 occurrences.

Known as term variance quality [37], this measure is an adaptation of the t v measure, but it aims at qualifying the variance of the words.

On the other hand, when a random sequence is modeled using any composition model, the actual variances of the word frequencies are the same with the variances predicted by the model; therefore, R is close to 1 in this case (approaching 1 as the sequence becomes longer).

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