Sentences with phrase «face value data»

Whether you get auto insurance quotes from a live person or through an online comparison engine, moving beyond the face value data and exploring various options can sometimes uncover a tidy sum of savings you may not have known existed.

Not exact matches

Besides collecting data on in - person interactions with sociometric badges, we gathered e-mail data to assess the balance between high - value face - to - face communication and lower - value digital messages.

Remington also has $ 250 million of bonds that come due in 2020, and are trading at a significant discount to their face value at 22 cents on the dollar, according to Thomson Reuters data, indicating investor concerns about repayment.

Taken at face value, the data for self - employed borrowers make no sense.

Combined data from the U.S. Census Bureau and the Federal Reserve allowed us to dive deeper into credit card debt in the United States, and look beyond the face value of those two figures.

Bonds issued by offshore unit HNA Group International were bid at 96.5 percent of face value, Eikon data showed on Jan. 12.

We do not, however, take these data at face value.

«Despite the efforts of teachers and pupils, the value of this year's test results will be poured over and questioned and schools face the prospect of being held to account unfairly on the basis of this year's results data.

Broader sharing of neuroscience data faces some technological hurdles, they said, but one of the major challenges is simply convincing researchers of the value of sharing the raw data with competitors in a timely fashion.

The nonexistent jobs crisis is a reminder of the dangers of taking government data at face value and using them for unintended purposes.

She accepts nothing at face value and does not have any particular agenda — just goes where her data and solid scientific logic lead her.

Taken at face value, the data in Table 3 rip the heart out of that advice.

Thus, without access to data supporting all teacher scores, any teacher facing discharge for a low value - added score will necessarily be unable to verify that her own score is error - free.

However, if a response only looked to me like it MIGHT have contained an error or two (such as a misplaced decimal point), I went ahead and took that author's reported data at face value.

Combined data from the U.S. Census Bureau and the Federal Reserve allowed us to dive deeper into credit card debt in the United States, and look beyond the face value of those two figures.

As for the U.S. financial system - particularly major banks - I am continually perplexed by the juxtaposition of tens of millions of underwater mortgages and millions of delinquent and unforeclosed homes, coupled with a set of FASB accounting rules (revised at the height of the recent crisis) that allows these debts to be carried at face value upon the discretion of the banks that report the data.

At Euclidean, we have always referenced this data in context of the challenges that value strategies face given that there have been (and will continue to be) high profile investments that turned out to be value traps.

So while we don't believe that the record high gold / XAU ratio can be taken entirely at face value, there's no question that it is elevated even on a cyclical basis (that is, even allowing for a gradual structural increase over time), and there's no question in the data that cyclically elevated gold / XAU ratios have been associated with strong subsequent gains in the XAU index over a 3 - 4 year period on average, though certainly not without risk or volatility.

While the data from Steam Spy was helpful to those who know how to crunch their numbers, it was misleading to those who took it at face value.

However taking Harrison and Stephenson's data at face value, the cloudiness as measured by the DF is completely independent of the CRF at values above 3600 (x100) per hour.

At face value, the satellite data is supported by weather balloon data, covers a much larger area of the globe than the surface - based data, and, as you pointed out, is free from the urban heat island effect and other potential flaws of surface measurements.

When taking into account all these kinds of factors, sometimes patterns emerge from cancer registry data that are invisible in the vagueness of the big picture; and sometimes patterns that seem significant on face value disappear.

You should be happy we even acccept that data at face value, with warts and all.

Even if one were to accept the agency's adjusted and manipulated «warmest on record» Goddard Institute of Space Studies incomplete surface temperature data at face value, NASA's claims about 2014 still make little sense.

Why not take the data at face value and see where it leads?

«People like Jim Hansen and Gavin Schmidt who sit up at the top of the climate food chain and take data from these weather stations at face value»...

People like Jim Hansen and Gavin Schmidt who sit up at the top of the climate food chain and take data from these weather stations at face value and then use it to extrapolate to nearby grid cells because there are no other nearby stations in the Arctic really need to get out more and see what the measuring environment is like.

As the interpretation of infinity in economic climate models is essentially a debate about how to deal with the threat of extinction, Mr Weitzman's argument depends heavily on a judgement about the value of life... A lack of reliable data exacerbates the profound methodological and philosophical difficulties faced by climate change economists... The United Nations conference in Paris this December offers a chance to take appropriate steps to protect future generations from this risk... http://www.economist.com/blogs/freeexchange/2015/07/climate-change (MOST COMMENTING ARE NOT AT ALL IMPRESSED)

I think a natural reply to both studies, even if one takes all data at face value, is «correlation is not causation».

It would be if those experts just took that data at face value.

The proper answer to 3) is «we don't know what the feedback is, but the evidence at face value suggests it is very small either way», but it is absurdly early days still as far as reliable data accrual is concerned.

So, we can't simply take the raw data at face value.

Moreover, taking the proxy sea surface temperature data for the peak Eocene period (55 — 48 Myr BP) at face value yields a global temperature of 33 — 34 °C (fig. 3 of Bijl et al. [84]-RRB-, which would require an even larger CO2 amount with the same climate models.

If the EECO global temperature exceeded 28 °C, as suggested by multi-proxy data taken at face value (see above), climate sensitivity implied by the EECO warmth and the PETM warming is close to the full Russell climate sensitivity (see electronic supplementary material, figures S7 — S9).

It was a straightforward paper reporting the trends of humidity in the middle and upper troposphere as they (the trends) appear at face value in the NCEP monthly - average reanalysis data.

I thought it would be like the 2005 hurricane papers, where the authors made conclusions based on the face value of flawed data.

As an aside: all those oh - so - skeptical people seem to be prepared to take the temperature data at face value when even the NASA says that there are lots of problems with the measurements which were only meant to be trial - runs.

The following is from the US Academies of Science in 2002 — from doyens of climate science — and can be taken at face value as a description of real world data.

Recommendations for verification are: 1) comparison to other models 2) degenerate tests 3) event validity 4) extreme event validity 5) extreme condition tests 6) «face» validity tests 7) fixed value tests 8) historical data validation 9) internal validity (stochastic runs) 10) multistage validation 11) parameter variability - sensitivity analysis 12) predictive validation 13) traces 14) turing tests (i didn't know what this is so googled ECWMF turing test, and i got 150 hits)

Once you get past the (semi-sensational) headline and into the post, Kevin makes a good observation about not taking Google Analytics data at face value.

Data I understand data as being a «given», something we accept at face value, raw facts like numbers, characters or imaData I understand data as being a «given», something we accept at face value, raw facts like numbers, characters or imadata as being a «given», something we accept at face value, raw facts like numbers, characters or images.

One of the key challenges facing organisations in the information age is the ability to take an organisational strategic approach to Information Governance to effectively maximise the value of information through data analytics while minimising its risks.

Regarding the company's acceptance at face value that Cambridge Analytica had deleted the data they weren't supposed to have (to Recode):

A question the potential for broader implementation is facing is whether Microsoft could get close to the same value for the end - user on third - party devices, given the limitations some face for data access.

We used these dimensions of differentiation because their face value of being «positive» and «negative» is high and unambiguous, unlike some other differentiation measures in the data set where there is ambiguity (e.g., preferred as caregiver, confidant, or the first - responder in a crisis).

This will help agents face two main challenges that affect pricing: (1) presenting consistent listing data representative of a home's green features, and (2) using that data to locate comparable properties, thus helping assign a more accurate value.

Additionally, more and more MLSs are recognizing the need and member value of an MLS consumer facing website; again, embracing the role and the power of being the primary source of accurate listing data.