A Quote by James D. Watson

No good model ever accounted for all the facts, since some data was bound to be misleading if not plain wrong. — © James D. Watson
No good model ever accounted for all the facts, since some data was bound to be misleading if not plain wrong.
Belief Systems contradict both science and ordinary "common sense." B.S. contradicts science, because it claims certitude and science can never achieve certitude: it can only say, "This model"- or theory, or interpretation of the data- "fits more of the facts known at this date than any rival model." We can never know if the model will fit the facts that might come to light in the next millennium or even in the next week.
So when someone, a veteran stands up and say, "Here are the facts on the VA." He [Donald Trump] says, "No, your facts are wrong." Turns out her facts are right and his facts are wrong.
I think it's my job or the artist's job, to try and find some solution or some reason to accept things. But given the grimmest reality, I feel the grimmest facts are the real facts, the true facts: that you're born, you die, you suffer, it's to no purpose, and you're gone forever, ever, ever, and that's it.
If you're living two lives and you're lying to everyone, you're bound to slip up, in some way, you're bound to get something wrong, and you're bound to get found out.
I was wrong to exaggerate in statements related to my experiences in the White House and the Royal Family. I am truly sorry for misleading people and misstating the facts.
Facts and data, rather than opinion, are the two cornerstones of problem solving, and yet they are consistently withheld from the people by American media. We must have facts and data in order to recognize where there is a problem!
We must start with scientific fundamentals, and that means with the data of experiments and not with assumed axioms predicated only upon the misleading nature of that which only superficially seems to be obvious. It is the consensus of great scientists that science is the attempt to set in order the facts of experience.
There are no surprising facts, only models that are surprised by facts; and if a model is surprised by the facts, it is no credit to that model.
I might show facts as plain as day: but, since your eyes are blind, you'd say, 'Where? What?' and turn away.
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.
There is a reasonable concern that posting raw data can be misleading for those who are not trained in its use and who do not have the broader perspective within which to place a particular piece of data that is raw.
A theory should not attempt to explain all the facts, because some of the facts are wrong
PowerPoint presentations, the cesspool of data visualization that Microsoft has visited upon the earth. PowerPoint, indeed, is a cautionary tale in our emerging data literacy. It shows that tools matter: Good ones help us think well and bad ones do the opposite. Ever since it was first released in 1990, PowerPoint has become an omnipresent tool for showing charts and info during corporate presentations.
I'm kind of fascinated by this idea that we can surround ourselves with information: we can just pile up data after data after data and arm ourselves with facts and yet still not be able to answer the questions that we have.
It is unrealistic to expect an entire profession to be completely good. There are bound to be some individuals who are stressed, who are unkind, who are a bit rubbish at their job, who are in the wrong career.
Good policy is grounded in a robust set of facts and data.
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