Sentence examples for actual variance from inspiring English sources

The phrase "actual variance" is correct and usable in written English.
It can be used in contexts related to statistics, finance, or any field where the concept of variance is relevant, typically to refer to the true or observed variance in data.
Example: "The actual variance in the dataset was significantly higher than the expected variance, indicating a greater spread of values."
Alternatives: "true variance" or "observed variance".

Exact(23)

This also highlights that ( {widehat{sigma}}_{Ri}^2 ) actually underestimates the actual variance of ( {widehat{boldsymbol{n}}}_{Ri} ) when assuming that it is an approximated Gaussian distribution.

Finally the values of the relative bias (RB) were obtained as the ratio of the bias, i.e., the expectation minus the actual variance, to the actual variance.

Finally, the actual variance of the RCS parameter estimation θ ̂ satisfies the CRLB.

Of course, whether such a theoretical possibility matters for the study of infectious diseases depends on the actual variance in degree for epidemiologically relevant contacts.

It is easy to see that the actual variance of θ ̂ and the CRLB do not change much as the SNR increases.

It is also easy to see that the actual variance of θ ̂ reduces as the number of radars increases from N=10 to N=20.

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Similar(37)

The weight of the a priori is determined by the balance between S y and S a. From a statistical point of view, the optimum value of S a would be the actual variance-covariance matrix of a priori (S e ).

Because SRSWOR tends to provide greater variances than OPSS, with OPSS equations (15) and (18) tend to overestimate the actual variances (21) and (23).

In contrast, the recovered variances were, on average, smaller than the actual variances (5 and 16 %, respectively).

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).

A post hoc power analysis with these 139 patients and the actual variances in CCQ scores showed that the power to detect a difference in change from baseline of 0.4 between the groups was 73% instead of 80%, which was aimed for.

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