Sentence examples for and strength of data from inspiring English sources
This little difference may be due to the time difference and strength of data collection.
A high degree of correlation obtained between the three biological replicates for all stages investigated underlines the reproducibility and strength of the data, which has also been validated by Q-PCR and in-situ hybridization analyses.
Given the consistency and strength of the data from the randomised controlled trials in adults, the assessment of effect size and risk of bias for GRADE assessment are based on data from randomised controlled trials alone, and the risk of bias for effects in adults was low.
The propositions were tested qualitatively by looking at the volume and strength of supporting or refuting data against each statement.
There is also a need for research into the all-important decisions that policy makers in different health systems make in terms of formula composition, including the strength of data and other information used for this.
Big Data's pursuit of "what" should be symbiotically linked to empiricism's pursuit of "why", which would increase the real strength of data analytics and accelerate scientific discovery collaboratively with empiricism.
But the Space Weather Prediction Center relies on the strength of data available, and right now there are only a few dedicated operational space weather-monitoring systems around the world.
Based on the comprehensive nature of the study, strength of data trends, and demonstrated sensitivity of the aquatic communities contained in the experimental system, the no-observed-effect concentration for HSAS was concluded to be 64.0 μg/L.
And so far it has demonstrated not the strength of data – that new religion – but its weakness.
19 Two reviewers (IJO and EAS) independently evaluated the level, quality and strength of the evidence, and extracted data.
Results are presented in Section 220 for 12 simulation scenarios, which differ according to the outcome variable (continuous or binary), amount and type of missing data and strength of predictors.
