Sentence examples for via statistical methods from inspiring English sources
Alternatively, local atomic configurations can be analyzed in an unbiased manner via statistical methods, providing information on local crystallography [25, 26].
In this regard, the six sigma is a methodology that enables the companies to review their existing status and guide them in making improvements by analyzing their status via statistical methods (Erbiyik and Saru 2015).
Since characterization of hundreds of genes is too large a task for detailed wet-lab experiments, capturing broad information via statistical methods is very helpful.
14 While not demonstrated via statistical methods, a smoother learning curve and earlier plateau in performance was noted in the group with feedback.
Eventually, this data should be gathered and often reduced to a single trajectory via statistical methods or analysed with data mining methods, that can be much more time expensive to be figured out than bare statistical estimators.
The generality of the improved formulas is verified via the statistical methods of bootstrapping and cross-validation.
With such designs, there are multiple, and substantially correlated, indices that can be integrated via new statistical methods to identify patterns of prenatal exposure.
Rather, system-driven approaches are viewed as supplementary to reductionist approaches, and can even include data derived via traditional statistical methods (Trochim et al. 2006).
Even though the dataset was small, we succeeded on characterizing the patients developing MOH and modeling our data via solid statistical methods highlighting important methods for assessing easy accessible clinical data in the prevention of MOH.
A multiple linear regression model was predicted via standard statistical methods to the database of n = 667 well samples, resulting in the model listed in Table 3 and shown in Eqs.
Therefore, for any given Λ there exists a large enough sample size that, if used to estimate confidence intervals, will yield significantly biased intervals that are difficult to correct via standard statistical methods.
