Sentence examples for statistical situations from inspiring English sources

So PM spaces offer a wider framework (than that of the metric spaces) and are general enough to cover even wider statistical situations.

In other words, the aforementioned t-test is equivalent to the likelihood ratio test under conditions of normality, as observed in several statistical situations (see, e.g., Lehmann and Romano 2005).

Though this works well in an 'ideal' statistical situation, problems arise when ITT is applied to complex clinical scenarios.

Turning to the %TBSA results, this is an unusual statistical situation, where despite a non-significant result, we seek to explore the possible degradation of predictive ability at high %TBSA resulting from our uncertainty over the effect of %TBSA.

As there are practical limits to achieving the perfect statistical situation of very large speckles, many applications of laser speckle for quantitative measurements use an analysis that recognizes that the maximum achievable contrast K max will be reduced by spatial averaging and other experimental factors.

A similar statistical situation was the CLARICOR (effect of clarithromycin on mortality and morbidity in patients with ischemic heart disease) study, in which the analysis of clarithromycin in patients with stable coronary heart disease showed also a non-significant hazard ratio [ 41], but the Food and Drug Administration reacted on that study with a warning notice.

Two related statistical models for situations involving finite or zero model/measurement error are devised.

The chapter demonstrates how to apply probability theory to gain insight into real, everyday statistical problems, and situations.

These parameters in turn make it possible to downscale or upscale all statistical moments to situations entailing smaller or larger measurement or resolution and sampling scales, respectively.

One possible path along which nature evolves and acquires its habits was explored by Peirce using statistical analysis in situations of experimental trials in which the probabilities of outcomes in later trials are not independent of actual outcomes in earlier trials, situations of so-called "non-Bernoullian trials".

In all situations statistical evidence is required to confirm that changes in BMI SDS effectively influence the risk of adult overweight.