Sentence examples for change variance from inspiring English sources

When the noise level increases the linear model that uses the footstep length's variance as the σ Δ v becomes less accurate than the other methods, but the linear model that uses step vector variance computed from the heading change variance with expected footstep length (0.7 m) according to Equation 58 is either on the same level or better than traditional models without known footstep length.

To be conservative, we assumed a correlation of 0.5 to impute missing change variance estimates in the primary analysis.

With these assumptions, accepting their limitations and using a change variance of 350 pg/mL, with alpha = 0.05, beta = (1-0.1 = 0.9) we require five subjects per group.

Among the studies in which 'pre-PMX-F,'post-PMX-F-F,' and change variance estimates were available, the median correlation between the two periods was 0.59 (range, 0.05 to 0.93).

Change in restraint and disinhibition were negatively (r = −0.53, P < 0.001) and positively (r = 0.39, P < 0.01) associated with change in body weight, accounting for 28.4 and 15.2% of body weight change variance, respectively.

Change in restraint and disinhibition were negatively (r = −0.44, P < 0.01) and positively (r = 0.31, P < 0.05) associated with change in energy intake, accounting for 19 and 9.3% of energy intake change variance, respectively.

In Figure 3B we show an example for a gene with a constant mean, but a changed variance in the two conditions.

Last year, Councilman Mitch O'Farrell proposed a citywide "value capture policy" that would require developers to build low-income units or pay into the city's Affordable Housing Trust Fund in exchange for zoning changes, variances or other exceptions that increase the value of the project.

The proportional change in variance (PCV) was calculated to evaluate how much of the variance in the first model is attributable to differences in individual characteristics [ 42].

The proportional change in variance [ 45] is another measure that could be used for explaining variance across hospitals by patient characteristics.

Observing the distributional changes, and percentage changes in variance, that result from such artificial causal interventions assist in making more realistic error variance assessments.