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Diagnosis of experimental data indicates that differences between theory and data may be explained through statistical analysis of error sources.
This paper addresses two key challenges: a domain challenge pertaining to an emerging climate services market, where users, tasks and data may be unknown; and an informational challenge pertaining to the interpretation, use and adoption of novel and complex scientific data.
While the sharing of email lists and data may be a common practice (especially in rallying political support and paying off campaign debt), the ethics are concerning.
Okay, this isn't exactly the most reassuring news in the world, but it does illustrate the point that cloud applications and data may be no more vulnerable than traditional systems.
Drawing upon recent theoretical innovations (Hagan et al., 1985; Jensen, 1993; Tittle, 1995), we propose that this apparent contradiction between theory and data may be reconciled by recognizing that SES has both a negative and a positive indirect effect upon delinquency that, in tandem, results in little overall correlation between the two.
These services may be invoked and data may be shared and integrated with other resources.
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Governments may lack the resources and capacity to field census and demographic surveys; and available data may be incomplete, intermittent, and unreliable.
A new study using X-ray data from the Chandra X-ray Observatory and XMM-Newton and SDSS data may be a step in that direction.
Typically, organizations do not have resources to compare the real cost of creating applications with and without an RA and historical data may be scarce.
Investing in emerging markets is inherently risky: macroeconomic and accounting data may be misleading, political and banking systems are not always stable, and exchange rates may fluctuate.
However, it provides a method to manage uncertainty and address forecasting concerns where rich and objective data may be lacking.
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