Sentence examples for confident evaluating from inspiring English sources
Computational limitations prevented the creation of a distribution of random models for each trait, but the difference in explanatory power between the random and full models was quite large (typically an order of magnitude, see results), thus we felt confident evaluating the strength of our models compared to one iteration of the random model.
Furthermore, trainees from surgical specialities felt more confident at assessing research evidence (p = 0.009), and medical speciality trainees felt more confident at evaluating statistical tests (p = 0.038) than those clinicians from other specialities.
Trainees from surgical speciality felt more confident at assessing research evidence (p = 0.009) whereas those from medical speciality felt more confident at evaluating statistical tests (p = 0.038) than other specialities.
Male trainees felt more confident at evaluating statistical tests than females (p = 0.002).
It was found on subgroup analysis that male doctors felt more confident at evaluating statistical tests than female doctors (p = 0.002).
Most trainees were confident or very confident in all evaluating items assessing confidence regarding smoking cessation work directly after the training program.
However, by focusing on peak-overlaps, we could concentrate our analysis on regulatory regions containing several peaks, even if each peak in the region was less confident when evaluated on its own.
He didn't even know my name, but felt confident he could evaluate my work.
Their experimental results showed that participants sitting with "confident" posture truly felt more confident about themselves, and held more positive self-attitudes when evaluating themselves as potential professionals.
The decision makers would be more comfortable and confident to give vague judgments rather than evaluating pairwise comparisons using single numeric values.
Respondents generally indicated that the majority of them did not feel confident at assessing research study design, generalisability, evaluating bias, sample size and statistical tests.
