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A prototypical example of self-normalized random variables is Student's t-statistic which replaces the population standard deviation σ in the standardized sample mean n ( X ¯ n − μ ) / σ by the sample standard deviation.
Consequently, the standard error, (text {se}(hat {vartheta })), of (hat {vartheta }) can be estimated by the sample standard deviation of the G replications, i.e., widehat{text{se}}(hat{vartheta}) = left{ frac{1}{G-1}sum_{g=1}^{G} left[hat{vartheta}_{g}^ - (hat{vartheta}_{1}^ + cdots + hat{vartheta}_{G}^)/Gright]^{2} right}^{1/2}.
All samples were centered by subtracting the sample mean and scaled by dividing by the sample standard deviation.
Prior to performing statistical analyses, the samples were centered by subtracting out the sample mean and scaled by dividing by the sample standard deviation.
In each centre, each quantitative variable was transformed into a z-score (equal to (observed value minus the sample mean), divided by the sample standard deviation).
If we think about a one-sided normal test for the mean, w can be identified as the distance between the null and the alternative mean values, normalized by the sample standard error of the mean.
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Alternatively, to find genes with expression variation across conditions, a user can set a ' coefficientcient of variation, given by dividing the sample standard deviation by the sample mean) filter, to only keep genes with a minimum required CV value.
We denote this estimate as. 4. Estimate the standard deviation of the background noise by calculating the sample standard deviation of the noise for values that are smaller than.
Secondly, the production status of the evaluated DMU in the 24th year is evaluated by the sample standards.
In practical situations, the population mean μ and standard deviation σ, if unknown, can be estimated by the sample mean and the sample standard deviation.
The constraint condition consists of one of the sample standards determined by the production strategy.
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by the sample water
by the sample morphology
by the sample covariance
by the sample holder
by the sample contrast
by the sample temperature
by the sample data
by the sample test
by the sample proportion
by the sample material
by the sample preparation
by the sample distribution
by the sample matrix
by the sample size
by the sample path
by the sample magnetization
by the sample fluorescence
by the sample return
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