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A z-score can be computed for each data value.
In applying equation 1, the deviation (difference) of each data value from the sample mean is computed and squared.
Each data value represents the average of three measurements.
However, if each data value of an attribute is the distinction, the number of possible cut points is (n-1).
To apply these results to linear interpolation between discrete data values, we need the ramp response function corresponding to the sampling interval τ between each data value.
Simplest type of digital filter replaces each data value f i by a linear combination gi of itself and some number of nearby neighbors: g_{i} = mathop sum limits_{{k = - n_{text{L}} }}^{{n_{text{R}} }} c_{n} f_{i + n} (1).
Similar(47)
The similarity measure of an input job (unseen) is calculated with each seen data value (except its seen priority value) of the scheduler.
For normalization, each sample data value was background-subtracted and normalized by the median of positive controls represented on the array.
The Markov Chain Monte Carlo method was used with a non-informative prior and a single chain to generate five imputes for each missing data value [ 35, 36].
Optimal thresholds were therefore calculated by performing univariate Cox regression for each measured data value and the threshold leading to the hazard ratio with the highest significance was taken as optimal cut-off.
When the same person is involved in each column's data value (i.e., a complete row of data is from the same person), the fancy term that is used is "repeated measures".
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com