Arthur Conan Doyle Quotes

If the data do not prove that indexing wins, well, the data are wrong.

We should be cautious about embracing data before it is published in the academic press, and must always avoid treating correlation as causation.

Realize that agendas drive data, not the other way round

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.

Take the situation of a scientist solving a problem, where he has certain data, which call for certain responses. Some of this set of data call for his applying such and such a law, while others call for another law.

I love data. I think it's very important to get it right, and I think it's good to question it.

There's a lot of power in executing data - generating data and executing data.

There is a tendency to mistake data for wisdom…

It is easy to lie with statistics. It is hard to tell the truth without it.

No one believes an hypothesis except its originator but everyone believes an experiment except the experimenter. Most people are ready to believe something based on experiment but the experimenter knows the many little things that could have gone wrong in the experiment. For this reason the discoverer of a new fact seldom feels quite so confident of it as others do.

Careful economic analysis does have one important benefit, which is that it can help kill ideas that are completely logically inconsistent or wildly at variance with the data. This insight covers at least 90 percent of proposed economic policies

Numbers can't speak for themselves, and data sets - no matter their scale - are still objects of human design.

The promoters of big data would like us to believe that behind the lines of code and vast databases lie objective and universal insights into patterns of human behavior, be it consumer spending, criminal or terrorist acts, healthy habits, or employee productivity. But many big-data evangelists avoid taking a hard look at the weaknesses.

Data and data sets are not objective; they are creations of human design. We give numbers their voice, draw inferences from them, and define their meaning through our interpretations.

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.

Philosophers of science have repeatedly demonstrated that more than one theoretical construction can always be placed upon a given collection of data.

To no circumstance is the wide diffusion of error in the world more owing than to our habit of adopting conclusions from insufficiently established data. An indispensable preliminary, then, in every investigation, is to get at facts. Until these are arrived at, every opinion, theory, or system, however ingeniously framed, must necessarily rest upon an uncertain basis.

The e-mails are mainly about a controversy over a particular data set and the ways a particular small group of scientists have displayed that dataset.

Data don't generate theory - only researchers do that.

Big data is indeed a buzzword but it is one that is frankly under-hyped.

scientists ... resist ... making more of the data than the data make of themselves.

Data really powers everything that we do.

If you torture the data long enough, it will confess.

If the statistics are boring, you've got the wrong numbers.

You can use data wrong. It's just like polling. There have been a lot of politicians who go conduct a poll to figure out what they believe.