Sentence examples for finding variance from inspiring English sources

You do this by going to the catalog and finding "mean(" or finding "variance(".

Significance (P) is the probability of finding a variance component and F-statistic that are greater than or equal to the observed values and was tested using a non-parametric approach (Excoffier et al. 1992), with at least 3,000 permutations of the dataset.

Significance (P) is the probability of finding a variance component and F-statistic that are grater than or equal to the observed values and was tested using a non-parametric approach (Excoffier et al. 1992), with at least 3,000 permutations of the dataset.

Sensitivities for each parameter were then established by finding the normalized variance (variance of the observations divided by the mean) in the ensemble means and standard deviations of individual ensemble model outcomes associated with that particular parameter.

Fama's findings were sought to be empirically validated by a significant body of research, ultimately finding that large variance in expected changes in the spot rate could only be accounted for by risk aversion coefficients that were deemed "unacceptably high".

The authors showed that IGF2/ H19 epigenotype and genotype independently account for 31% of the newborn's weight variance, finding no association with maternal diabetic status, glucose concentrations or prenatal maternal body mass index.

Go through finding the mean, variance, and standard deviation again.

If a way to measure inclusive fitness (especially as a function of a change in the level of gene expression) could be devised for an experimental system, an approach that mimics what has been done to detect sexually antagonistic fitness variance could be successful in finding parentally antagonistic fitness variance.

Recognizing that the solution lies on the two single-period frontiers, we may rewrite the problem as one of finding single-period variances v 1, v 2 to minimize V=v_{1}+v_{2}+chi v_{1}v_{2}+2v_{1}m_{2}+2v_{2}m_{ 1.

The replicate variance was omitted from the model after finding the non-significant variance between the replicates.

Instead of finding hyperplane of maximum variance between the input and response variables, it finds a linear regression model by projecting both variables to a new space (Boulesteix and Strimmer, 2007; Fornell and Bookstein, 1982; Lê Cao et al., 2008; Liu and Rayens, 2007; Tenenhaus et al., 2005).