Quotes on Data

[Women] tend to collect more pieces of data when they think, put them into more complex patterns, see more options and outcomes. They tend to be contextual, holistic thinkers.

All knowledge that is about human society, and not about the natural world, is historical knowledge, and therefore rests upon judgment and interpretation. This is not to say that facts or data are nonexistent, but that facts get their importance from what is made of them in interpretation… for interpretations depend very much on who the interpreter is, who he or she is addressing, what his or her purpose is, at what historical moment the interpretation takes place.

A point of view can be a dangerous luxury when substituted for insight and understanding.

When an economist says the evidence is "mixed," he or she means that theory says one thing and data says the opposite.

By definition, big data cannot yield complicated descriptions of causality. Especially in healthcare. Almost all of our diseases occur in the intersections of systems in the body.

It is better to have 100 functions operate on one data structure than to have 10 functions operate on 10 data structures.

Every good writer I know needs to go into some deep, quiet place to do work that is fully imagined. And what the Internet brings is lots of vulgar data. It is the antithesis of the imagination. It leaves nothing to the imagination.

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.

Still, it is an error to argue in front of your data. You find yourself insensibly twisting them round to fit your theories.

Quality without science and research is absurd. You can't make inferences that something works when you have 60 percent missing data.

Whole communities are growing up without fathers or male role models. Bringing up a family in the best of circumstances is not easy. To try to do it by placing the entire burden on women - 91% of single-parent families in Britain are headed by the mother, according to census data - is practically absurd and morally indefensible.

It is generally believed that our science is empirical and that we draw our concepts and our mathematical constructs from the empirical data. If this were the whole truth, we should, when entering into a new field, introduce only such quantities as can directly be observed, and formulate natural laws only by means of these quantities.

The implication that women are poised to make unfounded accusations in droves is even more alarming when every piece of data on false reporting contradicts that false notion. We need to believe women and believe in women.

It's easy to pretend expertise when there's no data to contradict you.

Obviously, a man's judgement cannot be better than the information on which he has based it. Give him the truth and he may still go wrong when he has the chance to be right, but give him no news or present him only with distorted and incomplete data, with ignorant, sloppy or biased reporting, with propaganda and deliberate falsehoods, and you destroy his whole reasoning processes, and make him something less than a man.

Science is composed of laws which were originally based on a small, carefully selected set of observations, often not very accurately measured originally; but the laws have later been found to apply over much wider ranges of observations and much more accurately than the original data justified.

I have the idea that running shoes are based on a kind of cult idea - that our feet are flawed and we need shoes to correct those flaws. The shoe companies are in the business of selling shoes. But there's no evidence from running shoe manufacturers that they're right. There's no scientific data that running shoes reduce injury.

Intuition becomes increasingly valuable in the new information society precisely because there is so much data.

What we call our data are really our own constructions of other people’s constructions of what they and their compatriots are up to.

Research can only present data about the past. No one seriously believes that people's answers to hypothetical questions about the future accurately represent their future behaviour; they merely represent a current attitude, which may or may not be translated into future behaviour.

You don't get to cut that chain of evidence and start over. You're always going to be pursued by your data shadow, which is forming from thousands and thousands of little leaks and tributaries of information.