Sentences with phrase «much science data»

Not exact matches

As much as your marketing guys want to learn data science, it's much, much easier to teach a data scientist the basics of marketing.

From cancer research and materials science to psychological profiles, these new data sets will even smaller players to innovate and compete with much larger organizations.

Jeffrey Pfeffer proclaims in this new book that «much of the oft - repeated conventional wisdom about leadership is based more on hope than reality, on wishes rather than data, on beliefs instead of science.»

We don't know much about the author other than he appears to have no professional financial background or qualifications, is well - qualified in computer science and claims experience in data science and simulation.

Nevertheless, it seems to be a very empirical way of beginning to understand the universe, more radically empirical in fact than science is itself.3 Here we are attending not only to the data of sense - perception but also to a much more proximate set of givens — the experiential components of our own subjectivity.

Science was not able to tell me why my son had to suffer so much, but it was also science that brought him relief from the seizures along with solid data collection by way of mediScience was not able to tell me why my son had to suffer so much, but it was also science that brought him relief from the seizures along with solid data collection by way of mediscience that brought him relief from the seizures along with solid data collection by way of medication.

Along with common human experience, the behavioral sciences provide much data that can only be explained in terms of the individual's fundamental desire to be valued.

Yet it must be granted that Whitehead's general orientation has been considerably and consciously shaped in terms of Christian insights, even though much of his general thought has been constructed from the data of science.

This is a good change and means the official data will more accurately reflect science and experimental technology development, but it also means the official R&D budget is now much smaller than it used to be.

«Sky surveys became respectable not only because they brought in so much data but because the content of the data was so high that it enabled so many people to do science.»

Much of the data contained in the below sections have been generated by AAAS, through analyses of the President's annual budget and Congressional appropriations, while other data is from other sources like the Organisation for Economic Cooperation and Development (OECD) and the National Science Foundation (NSF) National Center for Science and Engineering Statistics.

In challenging the multiple migration model, the new genome data, published online today in Science, suggest that Europeans today are the descendants of a very old, interconnected population of hunter - gatherers that had already spread throughout Europe and much of central and western Asia by 36,000 years ago.

Geospatial data scientist Lea Shanley, 2008 - 09 Congressional Fellow sponsored by ASA / CSSA / SSSA in the office of Sen. Bill Nelson, has devoted much of her career to citizen science.

«The only thing surprising in the data is how much the data from these absolutely brilliant women look like data from any group of high - achieving women in general,» says Diane Halpern, the dean of social sciences at the Minerva Schools at Keck Graduate Institute in California.

«It's frustrating because it should be a golden age of planetary exploration because there's so much data that's coming in, but what's missing is the commitment of funding to interpret the measurements,» says Jim Bell, associate professor of astronomy at Cornell University and a science team member on the twin Mars rover mission.

Actually Blue Brain is very much about reverse engineering, looking at all the data, standardizing the data, getting the information into a framework where we can even do correlation - based science on it, building automatic tools to synthesize those data into biological phenomena.

The data need to come much more from industry, not just from science labs.

Much social science consists of uncritical backward - looking references, not to established data but to speculations and contrivances into which their creators have squeezed carefully selected or invented «facts», references that are mere appeals to authority, admiringly called «scholarship».

«So there's much more demand for people who have the quantitative background in handling large [amounts of] health science data,» she says.

By contrast, Moitra and his coauthors — Gautam Kamath and Jerry Li, both MIT graduate students in electrical engineering and computer science; Ilias Diakonikolas and Alistair Stewart of USC; and Daniel Kane of USCD — found an algorithm whose running time increases with the number of data dimensions at a much more reasonable rate (or, polynomially, in computer science jargon).

But an in - depth analysis of grant data from the U.S. National Institutes of Health (NIH) on page 1015 in this issue of Science finds that the problem goes much deeper than impressions.

We need to use the best - available data, science and technology to reduce that footprint as much as we can.»

She quoted Edward Holmes, a leading scientist at the HIV - sequencing laboratory at the University of Edinburgh, as saying that using viral genetic data for forensic science is much more complex than other techniques, such as DNA fingerprinting.

In a revolution that extends across much of science, researchers are unleashing artificial intelligence (AI), often in the form of artificial neural networks, on the data torrents.

«The data has been used by every level of government to make decisions about the management of waterways from deciding which waters are impaired to determining how much nitrogen a specific estuary can handle,» said Rachel Jakuba, PhD, science director for the Buzzards Bay Coalition and a coauthor of the paper.

When a Nobel prizewinner threatens to sue colleagues, and when they deny his access both to the regular means of scientific publication and to the primary data on the basis of which his findings have been refuted, there must be much more going on besides matters of science.

Recent NSF data show that science and engineering journal article output worldwide grew at an average annual rate of 2.3 percent between 1995 and 2005, but the US growth rate was much lower, at an annual 0.6 percent.

The reason that today's big data sets pose problems for existing memory management techniques, explains Saman Amarasinghe, a professor of electrical engineering and computer science, is not so much that they are large as that they are what computer scientists call «sparse.»

«There's so much that we can learn from close - up spacecraft observations that we'll never learn from Earth, as the Pluto flyby demonstrated so spectacularly,» said New Horizons science team member John Spencer, of the Southwest Research Institute (SwRI) in Boulder, Colo. «The detailed images and other data that New Horizons could obtain from a KBO flyby will revolutionize our understanding of the Kuiper Belt and KBOs.»

The ATLASGAL survey is the single most successful APEX large programme with nearly 70 associated science papers already published, and its legacy will expand much further with all the reduced data products now available to the full astronomical community.

While there was a lot of interesting science in this paper (the new methodology, the range of results etc.) which fully justified its appearance in Nature, we were quite critical of their basic conclusion — that climate sensitivities significantly higher than the standard range (1.5 — 4.5 ºC) were plausible — because there is significant other data, predominantly from paleo - climate, that pretty much rule those high numbers out (as we discussed again recently).

SEI 2106 shows oodles of data that almost everyone will conclude is very solid evidence denying my prediction (i.e., since academic science in the US is doing such a productive job and provides so much of value to the public, then all must be excellent!).

I really appreciate how much work and thought you put into these topics, and especially how you encourage readers to consider the science and fully understanding the proper interpretations of experiments & data, etc..

The data on vacancies in the biological and physical sciences show much the same pattern.

It's important to note that science does not tell us what data we need to gather, or how much of it we need to have before it counts for something.

Our schools need to teach the real, discipline - based skills of quantitative data analysis, statistics, political science, and economics much better than they do now if we are to be prepared to wade into this maelstrom of information.

Our services have embedded research findings about distributed leadership, the science of learning, school ethos, the data intelligent school, the most effective strategies for CPD and much more.

Much of the data is that of TIMSS (see below)... Third International Math and Science Survey (TIMSS) An international database of 40 countries.

The art of marketing has become much more of a science, but even with acres of data and analytic... More

It is interesting to note that studies are showing we are more honest with technology than we are with doctors, and so this means anything tracking our health will amount to much cleaner data for the evolution of health science.

Is their position and no matter how much you point them at skeptical science or peer reviewed data, they only read the denial bunk and never read the quality data coming from such studies as these.

While there was a lot of interesting science in this paper (the new methodology, the range of results etc.) which fully justified its appearance in Nature, we were quite critical of their basic conclusion — that climate sensitivities significantly higher than the standard range (1.5 — 4.5 ºC) were plausible — because there is significant other data, predominantly from paleo - climate, that pretty much rule those high numbers out (as we discussed again recently).

There is no need to bet when you stick to the science (and measured data and observations as much as possible).

For their short lifetime on this earth these people actually believe that they have had that much effect while science and other data proves them wrong.

Working out these kinds of details is the process of science at its best, and many disciplines, not least mathematics, statistics, and signal processing, have much to contribute to the methods and interpretations of these series data.

Please, let's show at least this much respect for the «scientific method», as practiced in the physical sciences since the time of Sir Isaac Newton and Rene Descartes — in which a falsifiable hypothesis is tested against measurements of physical data!

I also hope that tussles at the edges of understanding, where data are scant or uncertainty is high, don't distract the public too much from the basics of climate science, which are boringly undisputed yet still speak of a rising risk that sorely needs addressing.

If the context behind the arguments is not included, the public just sees dispute, and can simply lump a science fight with those over abortion, gun rights, energy policy and other issues framed by ideology or values as much as (or more than) data.

Steven E. Koonin, once the Obama administration's undersecretary of energy for science and chief scientist at BP, stirred up a swirl of turbulence in global warming discourse this week after The Wall Street Journal published «Climate Science is Not Settled,» his essay calling for more frankness about areas of deep uncertainty in climate science, more research to narrow error ranges and more acknowledgement that society's decisions on energy and climate policy are based on values as much ascience and chief scientist at BP, stirred up a swirl of turbulence in global warming discourse this week after The Wall Street Journal published «Climate Science is Not Settled,» his essay calling for more frankness about areas of deep uncertainty in climate science, more research to narrow error ranges and more acknowledgement that society's decisions on energy and climate policy are based on values as much aScience is Not Settled,» his essay calling for more frankness about areas of deep uncertainty in climate science, more research to narrow error ranges and more acknowledgement that society's decisions on energy and climate policy are based on values as much ascience, more research to narrow error ranges and more acknowledgement that society's decisions on energy and climate policy are based on values as much as data.

Three themes are emerging from the newly released emails: (1) prominent scientists central to the global warming debate are taking measures to conceal rather than disseminate underlying data and discussions; (2) these scientists view global warming as a political «cause» rather than a balanced scientific inquiry and (3) many of these scientists frankly admit to each other that much of the science is weak and dependent on deliberate manipulation of facts and data.