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To demonstrate the sample sizes required to achieve various levels of statistical significance under different correlations, this manuscript presents plots of the distribution of P-values as a function of sample size.
We intend for this analysis to demonstrate the sample size necessary to detect a difference between an assumed ferret SAR of a future experiment and the lower threshold for a supercritical classification.
In Table 3, we demonstrate the sample sizes needed to detect the bladder cancer risk from lifetime arsenic exposure in females based on the NRC estimates and a background lifetime bladder cancer risk among females in the United States from the Surveillance Epidemiology End Results SEERR) data (NCI 2010), assuming 80% statistical power and a type 1 error (false-positive rate) of p = 0.05.
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Finally, two simulation and one experimental examples were used to demonstrate the sampling methodology.
A tubular reactor with recycle is used as illustrative example to demonstrate the sampling methodology, including cases where the system behaviour is unstable exhibiting sustained oscillations.
We take sampling of rural households in Changzhou as an example to demonstrate the sampling design, sample size calculation and response rate.
Table 5 demonstrates the sample sizes needed based on the choice of the primary endpoint for arbitrary but typical effect sizes.
This paper demonstrates the sampling, symmetry and zero-padding required to ensure that the window does not introduce any distortion of the waveform.
This variability in alpha scores demonstrates the sample-dependent nature of the statistic and supports the need for authors to continue to investigate the psychometrics of the DREEM.
We also demonstrate the feasibility of sample collection and laboratory sample processing protocols and techniques.
The EDS, XRD, and XPS characterization demonstrates the Cu sample was not oxidized during the sample preparation.
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CEO of Professional Science Editing for Scientists @ prosciediting.com