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In digital optical communications, BER, defined as the ratio of bits in error to total number of transmitted bits at the decision point, is commonly used as a figure of merit.
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Different allocations of biological and technical replicates were evaluated by minimizing the variance of the ratio of technical variance (measurement error) to the total variance (sum of sampling error and measurement error).
Because of the difference in scoring, different analyses were required: The reliability of the SCIP-A was analysed using the KR-20 formula: this provides an estimate of the degree of measurement error in the scale score ranging from 1.0 (no error) to 0.0 (total error).
I use the ratio of errors caught to total errors as a measure of effectiveness, which is 47.6percentt over the sample period.
Conventional test analysis has centred on the errors in reporting individual differences in ability, reporting a "reliability coefficient" as the summary of a test's accuracy, which is traditionally reported as a ratio of non-error variance to total variance.
We took the total error to be the sum of Type I and Type II errors for the isopleth in question; although for some applications, if the relative importance of Type I and II errors differs, a weighted sum can be used.
The material variability was combined with the measurement error to obtain the total covariance of the elastic constants.
An estimate of the BER is obtained as the ratio of the number of counted bit errors to the total number of bits transmitted P ̂ b ≜ 1 N ∑ i = 1 N F ( x i ).
A ratio comparing the number of morphological errors to the total number of morphological forms found in the transcript was used as the discourse-based measure of morphology.
The ANOVA technique allowed estimating the contribution of several sources of errors to the total variance in the DNA-microarray data of all slides.
The relay selection is optimized both by minimizing an error probability subject to total energy consumption and by the dual approach, minimizing total energy consumption subject to error probability constraints.
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