Quotes About Data

All of the studies we do in my group are quantified.

Much of what I do in my job is think about whether relationships we see in data are causal, as opposed to just reflecting correlations. It's exactly these issues which come up in evaluating studies in public health.

Traditionally, when you talk to people who have Parkinson's or Alzheimer's, they'll talk about how they're in five or six studies, and they've been sequenced by each study. That's just fat in the system. Just have a single data set that then you can share. You can make the entire system more efficient.

You can get a subjective and highly factual dossier on most anyone in the public realm almost instantly. It's why publishers don't worry about author photos any more; people just Google a person and get on with things.

Amazon is famously run by studying and responding to its own data; yet when it comes to promotions, decisions are often subjective and guided by human emotions and petty political dynamics.

The Trump campaign generally does not respond at all to my requests for information - either requests for broader data on Trump's charitable giving or narrow requests for information about specific subjects, like the $20,000 portrait of himself that Trump seems to have purchased with money from his charity.

Soon I knew the craft of experimental physics was beyond me - it was the sublime quality of patience - patience in accumulating data, patience with recalcitrant equipment - which I sadly lacked.

The Internet is a container, not a substance.

I'd aspired to give people a profound education - to teach them something substantial. But the data was at odds with this idea.

Risk models are a substitute for historical knowledge, because they tend to work with just three years' worth of data. But three years is not a long time in financial history.

There has been a substitution of ideology for fact and scientific and engineering data in this administration.

If you'd come to me in 2012, when the last presidential election was raging and we were cooking up ever more complicated ways to monetize Facebook data, and told me that Russian agents in the Kremlin's employ would be buying Facebook ads to subvert American democracy, I'd have asked where your tin-foil hat was.

By relying on the statistical information rather than a gut feeling, you allow the data to lead you to be in the right place at the right time. To remain as emotionally free from the hurly burley of the here and now is one of the only ways to succeed.

Today most of the debate on the cutting edge in macroeconomics would not call itself "Keynesian" or "monetarist" or any other label relating to a school of thought. The data are considered the ruling principle, and it is considered suspect to have too strong a loyalty to any particular model about the underlying structure of the economy.

In a different direction, the necessity to model the analysis of noisy incomplete sensory data not by logic but by Bayesian inference first came to the forefront in the robotics community with their use of Kalman filters.

Statisticians do it with confidence, frequency and variation

We are drowning in information and starved for knowledge.

Shakespeare's plays and poems in their entirety amount to 5 megabytes, the equivalent of just a single high-resolution photograph, or of 30 seconds of high-fidelity sound, or of 8 seconds of streamed high-definition video.

A record, if it is to be useful to science, must be continuously extended, it must be stored, and above all it must be consulted.

There will always be plenty of things to compute in the detailed affairs of millions of people doing complicated things.

Much needs to occur, however, between the collection of data and observations, the extraction of parallel material from the existing record, and the final insertion of new material into the general body of the common record. For mature thought there is no mechanical substitute. But creative thought and essentially repetitive thought are very different things. For the latter there are, and may be, powerful mechanical aids.

Science is the search for neat predictable curves, compact ways of summarizing the data. But there is danger that curves we see are illusory, like pictures of animals in the clouds. As we draw our self-propelling arcs, some points will inevitably lie outside the line—those that must be dismissed as random error or noise. So we are left with a gnawing dissatisfaction: Are we missing something?

the Social Security Administration has also kept a record.

The existence of matter and energy in the universe did not require the violation of energy conservation at the assumed creation. In fact, the data strongly support the hypothesis that no such miracle occurred. If we regard such a miracle as predicted by the creator hypothesis, then the prediction is not confirmed.