Sentence examples for data conversely from inspiring English sources

(iii) There does not appear to be an increase in the wealth shares of the top 1% or the top 10% between 2000 and 2010 in the raw data: conversely, Piketty's data shows a slight increase.

The tumour data, conversely [as shown by (x62, x63, x71, x73)] exhibited strong signals for a variant.

For smaller values of xmin, the credible region is reduced since there is more data, conversely increasing xmin to around 200 increases the credible regions slightly.

If the summary statistics for the testis are within the range of summary statistics for the simulations then the model is consistent with the data; conversely, if the summary statistics for the testis are outliers for the range of summary statistics in the simulations then the model is rejected (19– 219.

This destabilization had an impact on the trace element distribution in soil solution, as assessed by REE data, and conversely, the destabilization degree of humic substances seemed to be influenced by the metal ion charge.

At the scale of the mountain belt, drainage basin metrics such as relief, hypsometric index and slope values seem to explain the observed variance in the data population, conversely to the first-order average precipitation pattern, suggesting a strong tectonic control on the regional pattern of denudation rates.

The human-based approach is via a survey in a community or by questioning other members who can help to determine the reputation of a source or by the person who published a data set; conversely, the (semi-) automated approach can be performed by the use of external links or page ranks.

The previous data quantified, conversely to our study, circulating EPCs in whole blood with only three surface markers (CD34/CD133/VEGFR-2) [ 8- 16, 16].

The resulting scatter plot demonstrates the variability of some RNA-seq data (and, conversely, the remarkable consistency of the GEUVADIS data), and strongly signals that a single heuristic for such diverse data may not be appropriate.

In other words, it is unlikely that the prediction models in this study have captured the peculiarities in this data set; conversely, it is likely that predictions, based on this data, will be generalisable to other, similar populations.

In this way, we can see how the analysis methods perform under differently simulated data and, conversely, how important the choice of simulation model is when assessing performance of such methods.