Data Quotes - Page 19

A problem of statistical inference or, more simply, a statistics problem is a problem in which data that have been generated in accordance with some unknown probability distribution must be analyzed and some type of inference about the unknown distribution must be made.

As the data from the past decade clarify, there is no evidence that poverty causes crime but a great deal of evidence that crime causes poverty. By aligning themselves against the police, against commonsense tactics like stop and frisk, against metal detectors in public housing, against swift and certain punishment, and for a broad array of legal protections for accused criminals, liberals helped to aggrieve the lives of the poor and society as a whole.

The USA Freedom Act does not propose that we abandon any and all efforts to analyze telephone data, what we're talking about here is a program that currently contemplates the collection of all data just as a routine matter and the aggregation of all that data in one database. That causes concerns for a lot of people... There's a lot of potential for abuse.

I hold that the propositions embodied in natural science are not derived by any definite rule from the data of experience, and that they can neither be verified nor falsified by experience according to any definite rule.

Data is just like crude. It’s valuable, but if unrefined it cannot really be used. It has to be changed into gas, plastic, chemicals, etc to create a valuable entity that drives profitable activity; so must data be broken down, analyzed for it to have value.

What gets measured (and clearly defined) does get done.

Even the best data security systems can't protect private taxpayer information from entrepreneurial foreign businesses than can make huge profits selling U.S. taxpayer information.

All research in the cultural sciences in an age of specialization, once it is oriented towards a given subject matter through particular settings of problems and has established its methodological principles, will consider the analysis of the data as an end in itself.

Because we're always more woundable when caught at exactly the time where we're in the mood for that particular product or service - and as Big Data increasingly are able to pick up on clues revealing desire - automated systems are increasingly able to hit at exactly those moments, across those channels we move - with an offer matching exactly what we're desiring.

The religion of Big Data sets itself the goal of fulfilling man's unattainable desires, but for that very reason ignores her attainable needs.

He’s totally different from the typical jock. He has no ego. That’s unique for someone with such accolades. His strength comes from a higher power. You can’t explain Steve Largent by computer – he doesn’t belong on an NFL field. You put his size and speed in an IBM computer up in Silicon Valley, it would chew up his data card and laugh.

Maybe we, the cultural workers , could apply ourselves. We're not going to resolve it in this moment or even in this generation, but perhaps as some kind of agenda we could invite our writers and cultural workers to address the problem a little more responsibly, because people are suffering tremendously from a want of data.

Data-driven statistics has the danger of isolating statistics from the rest of the scientific and mathematical communities by not allowing valuable cross-pollination of ideas from other fields.

While the creative works from the 16th century can still be accessed and used by others, the data in some software programs from the 1990s is already inaccessible.

We've already seen shifts happening in some of the big companies - Google, Apple - that now understand how vulnerable their customer data is, and that if it's vulnerable, then their business is, too, and so you see a beefing up of encryption technologies. At the same time, no programs have been dismantled at the governmental level, despite international pressure.

We chose it because we deal with huge amounts of data. Besides, it sounds really cool.

Data that is loved tends to survive.

Unlike earlier thinkers, who had sought to improve their accuracy by getting rid of error, Laplace realized that you should try to get more error: aggregate enough flawed data, and you get a glimpse of the truth. "The genius of statistics, as Laplace defined it, was that it did not ignore errors; it quantified them," the writer Louis Menand observed. "...The right answer is, in a sense, a function of the mistakes.

You can't publish a paper on physics without the full experimental data and results; that should be the standard in journalism.

So ensuring the integrity of the data and integrity and validity of the connection is a very important element in any company's strategy that is moving towards a Web service paradigm.

TIA was being used by real users, working on real data - foreign data. Data where privacy is not an issue.

Uncontrolled access to data, with no audit trail of activity and no oversight would be going too far. This applies to both commercial and government use of data about people.

You can lead a horse to water but you can't make him enter regional distribution codes in data field 97 to facilitate regression analysis on the back end.

Our ability to do great things with data will make a real difference in every aspect of our lives.

Using TrackMan is very important in the development of your golf game because it gives you such good data on what your golf swing is doing and where it needs to go.