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The minimum number of samples for achieving relatively accurate results using the derived CRLB is a very important issue.
To avoid unnecessary numbers of samples for achieving adequate power, variance of the measurement technique should thus always be well below biological variance.
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Taking the size of the largest group as most precisely correlating to the sequence length sampled, for achieving the above mentioned condition one should take the sequence length of (10.4/8) × 1091 = 1417 units.
After the burn-in period, the number of samples needed for achieving a certain estimation accuracy can be determined from the Gaussian approximation given by the central limit theorem (see Theorem 1).
Moreover, it is very important to choose a sampling frequency for achieving the frequency down-conversion.
The necessary sample size for achieving acceptable statistical power was calculated to detect moderate effect sizes between the WHC arm versus the combined control arms ranging from 0.26 to 0.50 for the primary outcome, biologically confirmed drug abstinence.
Then, the overall system including source, collimator and sample was simulated for achieving radiographic images of standard samples.
Theoretically, calculating the sample size required for achieving the desired power is straightforward with true CV estimates and true test/reference GMRs of selected parameters.
Considering large sample volumes required for attaining low limits of these hormones, present method provides an ease for analyst as 10 mL of the sample is adequate for achieving the same sensitivity.
Theoretically, calculating the sample size required for achieving the desired power is straightforward with true coefficient of variance (CV) estimates and true test/reference geometric mean ratios (GMRs) of selected parameters.
On the basis of published estimations of sample size needed for achieving adequate power to detect association our data set has limited power.
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