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Direct comparisons of results among studies were hampered by the use of different statistics (medians, means, or geometric means) and sampling strategies; the use of standardized methods could strengthen the validity of results and facilitate comparisons among different populations and locations.
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Sample means and sample standard deviations were used on estimated coefficients of variation δ ̂.
The standard plug-in rule estimates the discriminant from a feature-label sample to obtain an estimate of the discriminant by replacing the means and covariance matrices by their respective sample means and sample covariance matrices.
Table 1 shows the means and sample standard deviations for answers to questions relating to career satisfaction, emotional states and perceived levels of job stress.
Other assumptions, such as that sample means and sample variances must be statistically independent, can be compensated when the sample is moderately large or larger, which is always the case for HCS.
Let us now define the sample means and the sample variances of the received samples, which will be used in the rest of the paper.
The sample means and the sample variance-covariance information can be found in Table 1.
Calculate sample mean and sample variance of the values in throughput vector. 5.
Different values xi from the corresponding intervals lead, in general, to different values of the sample mean and sample variance.
This principle is violated by the conventional fitting of normal or lognormal distributions using sample mean and sample variance.
However, similarly to sample mean and sample variance, the standard EPE approach is non-robust towards outliers [21 23].
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