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This variation on data access is exploited to reduce the overheads associated with data access by the virtual machines during jobs execution.
The effect of such variation on data quality requires further assessment, in which this would mandate an independent study with sufficient sample size that allows reliable comparison between the data collected by the two approaches.
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All the procedures were standardised to limit the impact of experimental bias or biological variations on data.
The objectives of this ecological study were to identify potential, country-level, socioeconomic determinants of pandemic A (H1N1) 2009 mortality and explain between-country variation, based on data from a total of 30 countries of the European Union (EU) and the European Free Trade Area (EFTA) on which we have complete data on variables of interest.
A variation on usual data mining algorithms, originally designed to mine static data, is proposed so that contextual and visual data at adaptive granularity levels can be mined.
Values based on untransformed data are shown since estimates of the coefficient of variation on transformed data are difficult to interpret (Houle 1992).
By defining two separate regimes of film thickness variation, roughness and unevenness, in relation to the crack spacing, the influence of such variation on the data is analysed.
To assess the effect of normalization on variation for data in Figure 7 we calculated IQR for M values of identified populations.
If the solution does not depend "smoothly" on the problem data, small variations on the data could create huge variations on the solutions, resulting in strong instability which is not acceptable.
Strengths of this analysis are its large size (including data from more than 2000 patients treated with basal insulin in 11 clinical trials evaluated in the pooled analysis), wide geographic variation and reliance on data from prospective, controlled trials.
For example, maternal plasma lipids were calculated as follows: Maternal plasma lipids (g/L) i = Average maternal plasma lipid concentration × Maternal plasma lipid multiplier i, [2] where i indexes "subject" (i.e., Monte Carlo iteration) and using the coefficient of variation calculated based on data from Glynn et al. (2011) as the SD of the multiplier distribution.
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