Paolo Bacigalupi Quotes

While data can only tell you what has happened in the past, it can in some ways give you a sense of what might be of interest to an audience in the future.

Prediction is very difficult, especially if it's about the future.

Predictions are hard, especially about the future.

I was interested in data mining, which means analyzing large amounts of data, discovering patterns and trends. At the same time, Larry started downloading the Web, which turns out to be the most interesting data you can possibly mine.

People believe the best way to learn from the data is to have a hypothesis and then go check it, but the data is so complex that someone who is working with a data set will not know the most significant things to ask. That's a huge problem.

If you have to forecast, forecast often.

The way that organizations and organisms anticipate the future is by taking signals from the past, most the time.

The key to making a good forecast is not in limiting yourself to quantitative information.

I figure lots of predictions is best. People will forget the ones I get wrong and marvel over the rest.

Science fiction is about extrapolation, looking back through history, spotting a trend, and predicting where it will go.

Analytics is not about sitting behind a computer and pushing enter and having it produce an answer.

The job of the data scientist is to ask the right questions.

Well, we'll look at the hundred thousand type A personalities, and then we'll have a look at the corresponding data points that we have on those hundred thousand people. We'll have a look at what attributes they have in common and then we'll build a model based on that.

Networks love data. They love to be able to look at numbers and try to predict what they think will work.

To learn something from your data, the forming of a hypothesis lies with the human being, which turns into a query, which becomes a result. The problem is that there are too many queries to make, too many questions to ask.

Till facts are grouped & called there can be no prediction. The only advantage of discovering laws is to foretell what will happen & to see bearing of scattered facts.

Some people hate the very name of statistics, but I find them full of beauty and interest. Whenever they are not brutalized, but delicately handled by the higher methods, and are warily interpreted, their power of dealing with complicated phenomena is extraordinary. They are the only tools by which an opening can be cut through the formidable thicket of difficulties that bars the path of those who pursue the Science of Man.

The business of the statistician is to catalyze the scientific learning process.

Trying to analyze a situation without enough data was like looking at a photograph of a ball in flight and trying to gauge its direction. Is it going up, down, sideways? Is it about to collide with a baseball bat? Is it moving at all, or is something on the blind side holding it in place? A single frame didn't mean a thing. Patterns were based on data. With enough datapoints, you could predict just about anything.

The only useful function of a statistician is to make predictions, and thus to provide a basis for action.

Charts are great for predicting the past.

If we start to use social media data sets to take the pulse of a nation or understand a crisis - or actually use it to deploy resources - we are getting a skewed picture of what is happening.

The premise and promise of Big Data is that there are no stories, only patterns; that the human preference for story is aligned with the human tendency for error; and that only through dislocations in scale - the scale of sample size and of time - will truth emerge.

The big mystery of Big Data is causation versus correlation.

I'm an analytics girl.