Sentence examples for more robust statistics from inspiring English sources

The discrepancy between the number of sites identified by the analysis of the single genes and the concatenated maxgen dataset may be related to more robust statistics when larger numbers of codons are involved in the analysis.

By grouping together the different Lutzomyia species we are considering association between a given mammal species and the different species of the Lutzomyia genus present in Mexico, rather than with individual species, thus increasing the sample size and allowing for more robust statistics.

We make no assumptions of the data distribution and use MADe, a factored Median Absolute Deviation (MAD), which has more robust statistics compared to standard deviation-based statistics and is largely unaffected by the presence of extreme values [57] [58] (see Materials And Methods section).

Because using ranks resulted in more robust statistics [ 23], we used Spearman correlation to assess the relationships between kits.

Applying the Empirical Bayes analysis (more robust statistics), systematic variation in CS is still higher than in NCS (between 1.8 to 3 times higher).

To increase the number of nuclei and to obtain more robust statistics, we nucleated Snf7 assemblies by adding 1 μM ESCRT-II and 1 μM Vps20 to a 75nMM Snf7 solution.

The use of the most recent generation of PET/CT or PET/MR scanners with a larger axial field of view and correspondingly higher sensitivity, time of flight capability and more robust counting statistics, might enable the use of a higher time resolution and higher doses.

IRT is more useful since it provides more robust item statistics that are independent and invariant over sample populations that vary in the trait measured by the test.

The AC1 statistics is more robust than K statistics and has therefore been recommended as an alternative or complement to K[ 25].

Robust statistics, more specifically, the stability theory of statistical procedures, systematically investigates the effects of deviation from modeling assumptions [17 19].

This makes the statistics more robust.