A Quote by Hans Selye
Random search for data on ... off-chance is hardly scientific. A questionnaire on 'Intellectual Immoralities' was circulated by a well-known institution. 'Intellectual Immorality No. 4' read: 'Generalizing beyond one's data'. [Wilder Dwight] Bancroft asked whether it would not be more correct to word question no. 4 'Not generalizing beyond one's data.
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No generalizing beyond the data, no theory. No theory, no insight. And if no insight, why do research.
In my view, our approach to global warming exemplifies everything that is wrong with our approach to the environment. We are basing our decisions on speculation, not evidence. Proponents are pressing their views with more PR than scientific data. Indeed, we have allowed the whole issue to be politicized-red vs blue, Republican vs Democrat. This is in my view absurd. Data aren't political. Data are data. Politics leads you in the direction of a belief. Data, if you follow them, lead you to truth.
Scientific data are not taken for museum purposes; they are taken as a basis for doing something. If nothing is to be done with the data, then there is no use in collecting any. The ultimate purpose of taking data is to provide a basis for action or a recommendation for action. The step intermediate between the collection of data and the action is prediction.
My answer to someone who is in contrast with me - by not seeing God in the scientific data - is that you don't see God in the scientific data because you're not me. I have other experiences than you have, that bring me to look at this data as enriching my experience of God.
People think 'big data' avoids the problem of discrimination because you are dealing with big data sets, but, in fact, big data is being used for more and more precise forms of discrimination - a form of data redlining.
Search engines generally treat personal names as search terms like any others: Data is data.
We tend to assume that data is either private or public, either owned by one person or shared by many. In fact there's more to it than that, above and beyond the upsetting reality that private data is now anything but.
Data isn't information. ... Information, unlike data, is useful. While there's a gulf between data and information, there's a wide ocean between information and knowledge. What turns the gears in our brains isn't information, but ideas, inventions, and inspiration. Knowledge-not information-implies understanding. And beyond knowledge lies what we should be seeking: wisdom.
The biggest mistake is an over-reliance on data. Managers will say if there are no data they can take no action. However, data only exist about the past. By the time data become conclusive, it is too late to take actions based on those conclusions.
It is not a medicine. You don't know what's in it. If there were compelling scientific and medical data supporting marijuana's medical benefits that would be one thing. But the data is not there.
We are now at a point in time when the ability to receive, utilize, store, transform and transmit data - the lowest cognitive form - has expanded literally beyond comprehension. Understanding and wisdom are largely forgotten as we struggle under an avalanche of data and information.
One of the myths about the Internet of Things is that companies have all the data they need, but their real challenge is making sense of it. In reality, the cost of collecting some kinds of data remains too high, the quality of the data isn't always good enough, and it remains difficult to integrate multiple data sources.
A data scientist is that unique blend of skills that can both unlock the insights of data and tell a fantastic story via the data.
Few intellectual tyrannies can be more recalcitrant than the truths that everybody knows and nearly no one can defend with any decent data (for who needs proof of anything so obvious). And few intellectual activities can be more salutary than attempts to find out whether these rocks of ages might crumble at the slightest tap of an informational hammer.
Data!data!data!" he cried impatiently. "I can't make bricks without clay.
I'm going to say something rather controversial. Big data, as people understand it today, is just a bigger version of small data. Fundamentally, what we're doing with data has not changed; there's just more of it.
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