Sentences with phrase «example of the actual data»

What's an example of the actual data stored in the blockchain for a Bitcoin transaction?

Not exact matches

For example, these returns involve the use of index data and do not represent actual trading results and there are no deductions for any fees, etc..

His category of transmutation describes the perceptual device which permits us to prehend the many actual entities of a nexus as one datum, so that trees or tables, for example, are grasped as trees or tables, rather than as myriad individual atomic actualities.

He does not distinguish properly, for example, between the abstract non-temporal divine valuation «linking possible situations (containing many data) to the best possibilities of synthesis of those data,» and the concrete divine evaluation or actual choice of a specific initial aim in the light of what has just happened in the world and thus been prehended by the divine consequent nature («Consequences» 330).

Reporting for the Excelsior Jobs Program is a good model to follow because it includes most of the metrics necessary to have a complete picture of recipients» commitments, actual performance, and incentives issued.3 Another good example is the downloadable data on Industrial Development Agency (IDA) projects provided on the Office of the State Comptroller (OSC) website, although quality metrics should include annual numbers, and not just totals.4 See Appendix A for a recommended list of metrics.

A study published in March 2015 in the Journal of the American College of Cardiology cites clinical data showing that even in the absence of an actual increase in blood pressure, excess sodium in the diet could harm the body, including blood vessels (for example, increased arterial stiffness), the heart (enlarged heart muscle), the kidneys (reduced renal function), and the brain (adverse sympathetic nervous system reactions).

For example, we will not be liable to you for any of the following types of damages, whether in contract, tort (including negligence and strict liability) or otherwise (whether such loss or damage was foreseeable, known or otherwise): (i) loss of revenue; (ii) loss of actual or anticipated profits; (iii) loss of the use of money; (iv) loss of anticipated savings; or (v) loss or corruption of, or damage to, data, systems or programs.

Lisa Castaneda's Forget Aperture, This is My Test Chamber — Data and Statistics Final Project is a great example of how teachers can use this powerful game - based learning tool to engage students in the actual doing of math and science.

This section also presents the actual evaluation process with examples of evidence and data sources to assist users in the development of the Professional Development Plan (PDP), including all requirements and a definition of key terms.

For example, data from Lipper, Inc. indicated that 1,460 new mutual funds were started in 2003, 2,309 in 2002, and 2,392 in 2001.1 The actual number of truly new and distinct funds is smaller, because Lipper counts different share classes as separate funds.

Steam's example is no doubt extreme, but we need to see the actual data they start using to enforce to truly judge it - as of now, it's all speculative.

Along those lines, has the following been tried (again, forgive if I'm asking something with an obvious answer published somewhere): 1) pick starting projection dates and subsequent run paths 2) example for (1): start 1980, run forward 5 years; start 1982, run forward 5 years; start 1984 (run to 1989) etc etc 3) at each start we proceed as with the 1979 directive; ie calibrate with several months of starting year data 4) thus the latest such (example) run where we could compare against actual data would be an initialization in 2008 and run forward for 5 years to 2013 5) the advantage of the above (and I recognize that there is a huge amount of work involved in crunching these simulations) is that we could see the starting temp and 5 year projections against the historical record for a number of overlapping segments.

Versus the typical climate science example where they don't use any actual data — they just make it up and ignore the actual data, or they use some climate model simulation of a fantasy climate.

So please give an example where measurements of any given phenomenon were taken, with a potential error range of the equivalent of + / - 5 % that you stipulated in the initial measurements, where that poor initial data was processed using statistics, and provided an «actual average measurement within + / -.03 %, that was then verified against later, with subsequent more accurate measurements.

The effects of this uneven sampling are being investigated and quantified in several ways, for example by estimating «true» global - mean temperatures from the complete fields generated by satellite observations, blends of satellite and in situ data, or climate models, and then sampling these fields using the actual (incomplete) observed data coverage (see chapter 9).

For example, the IEC defines a Class IA wind turbine to be designed to withstand a turbulence intensity of 16 percent at a wind speed of 15 m / s over its design lifetime.5 Turbulence intensities can be computed from wind data recorded at the wind - turbine site and are compared with the design values, providing another metric for quantifying the margin between design and actual wind conditions.

(For example, if we resampled the data, we might end up with a 66 % interval of 3 - 7.8 C, which would be neither more nor less likely to contain the actual value than 1 - 6 C.)

This hypothesis has yet to be validated by empirical data based on actual physical observations or reproducible experimentation and has not yet successfully withstood any attempts at falsification, so (unlike your example of «evolution») remains an uncorroborated hypothesis, rather than «reliable scientific knowledge» (or, even less, «settled science», despite what Gavin has stated in the past).

This is from an actual blog post by Dave Manuel (this seems to be such a common data analysis fallacy that I found an example on the first page of my first Google search).

The distinct issues of: (1) the number of persons traveling by air who are required by the airlines to be accompanied by an attendant, and (2) travel propensity, are further examples of how the carriers» tactical decision to withhold actual data meant the parties, and ultimately the Agency, had to engage in a lengthy and complex analysis based on less than ideal data.

For example, because Ad - Supported Users self - report their names and dates of birth, the personal data we have may differ from our Ad - Supported Users» actual names and ages.

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