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In the method of deterministic geostatistics (sensu Isaaks and Srivastava, 1988), highly-resolved data sets are used to compute sample spatial-bivariate statistics within a deterministic framework.
And, after pixel selection, the number of pixels which are used to compute sample covariance matrix is βL, where 1 ≤ β ≤ ( N/L ), so the number of multiplication will be βα 2 L 3. The number of multiplication reduced is ( N – βα 2 L ) L 2 – ( αL ) N. Let speed-up ratio be a, then a = NL /( βα 2 L 2 + αN ), where N » L, and 0 ≤ βα 2 ≤ 1, so a will be a very large number.
Thus, we could not provide a specific estimate of the statistical power used to compute sample size, so the results should be considered as hypothesis generating rather than confirmatory.
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Data collected from a simple random sample can be used to compute the sample mean, x̄, where the value of x̄ provides a point estimate of μ.
RNAsubopt was used to compute a sample of 1000 suboptimal structures within the 5% from the MFE.
The parameters used to compute the sample size were: proportion of ART adherence among HIV-infected children in Addis Ababa, Ethiopia 86.9% [ 11], 95% confidence level and a 5% margin of error, which provide a sample size of 175.
We also illustrate how these procedures may be used to compute power and sample sizes to design studies with response variables that are overdispersed count data.
A formula by Taro Yamana (Glenn 1992) was used to compute the appropriate sample size for the study, taking into consideration the projected number of households of the selected communities.
The power analysis was used to compute the required sample size.
The outcome of this procedure was used to compute, for each sampled mother, the proportion P c of offspring that could result from pollination by the cultivated variety.
The resulting 12 RA expression vectors were then used to compute pair-wise tissue sample correlations, of which the average values within and across the two tissues and technologies are plotted in figure 2. Both technologies show good reproducibility within the same tissue shown by the high correlation values.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com