Sentence examples for inferred no from inspiring English sources

A sense probe was generated for the Slc17a9 as a negative control and it inferred no signal.

Statistically, we inferred no positive effect in BT474 at all, which is explainable by the fact that we just considered a combined effect of drug treatment and time.

For efficiency, we then averaged the matrices across SNPs between which GAIN inferred no recombination in the population, and this reduced the mapping dataset to 27,059 intervals.

For computational efficiency, we then averaged the matrices across SNPs between which GAIN inferred no recombination in the population, and this reduced the mapping dataset to 27,059 intervals.

We therefore inferred no meaningful shift in the genome size measurements for specimens stored in silica for six months and thus genome size estimates obtained from four 6 month old silica samples (A.formosum, RD157 and RD158; spec.nov.1, RD162; and spec.nov.2, RD163), were used in all analyses as no fresh material was available.

"If one country in the monetary union can default, so can another — that is one simple inference that bank managers and hedge fund mangers can infer, no matter what Mrs. Merkel or Mr. Sarkozy may say," said Costas Lapavitsas, an economist at the University of London, referring to Chancellor Angela Merkel of Germany and President Nicolas Sarkozy of France.

This study infers no statistical significant difference in KS clinical and functional outcomes between two age groups (p value >0.05) (Table 3).

Under a null hypothesis of no effect, two kinds of errors in interpretation are possible inferring an effect where none exists (Type I error) and inferring no effect when in fact one exists (Type II error).

The F Ratio value calculated from ANOVA: single factor is lesser than 1 and F Ratio is lesser than F Crit, in both the experiments, inferring no significant difference between the three pertained methods.

Also congruent with [ 42], we infer no genetic barriers within the Atlantic Coastal Plain.

The first goal is minimizing type I error (essentially a false positive finding or inferring an effect exists when none actually exists) as well as type II (a false negative finding or inferring no effect exists when one actually exists).