Steven Levitt Quotes

I've said many times that I'm not one of those people who check statistics, follows history, and says, 'If I do this, what will happen.'

I'm not too worried about that. I am a big believer in modeling.

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.

After all, the past is our only real guide to the future, and historical analogies are instruments for distilling and organizing the past and converting it to a map by which we can navigate.

The combination of some data and an aching desire for an answer does not ensure that a reasonable answer can be extracted from a given body of data.

Managers used to say, 'I have a gut feeling.' Do you know what a gut feeling is for a professional manager? It's a pattern that they recognize. But if your system can recognize that pattern, if it's not just a couple of managers who know that pattern, then the system's gut feeling can tell you which way to go. That's really liberating.

Averages are useful because many traits, behaviors, and outcomes are distributed in a bell-shaped curve, with most results clustered around the middle and a much smaller group of outliers at the high and low ends.

Watson augments human decision-making because it isn't governed by human boundaries. It draws together all this information and forms hypotheses, millions of them, and then tests them with all the data it can find. It learns over time what data is reliable, and that's part of its learning process.

I learned analytics. It's a point of reference, of information. It has to be a factor in decision making.

Data is a tool for enhancing intuition.

Every day we go over data and use science and data to drive policy and decision-making.

Whether baseball or football, we're tasked in front offices with making decisions under uncertainty. How do you corral that uncertainty in a way to make more consistently better decisions? That's very similar.

In disciplines as disparate as baseball, financial services, trucking and retail, people are realizing the power of data to help make better decisions.

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.

Finding patterns is easy in any kind of data-rich environment; that's what mediocre gamblers do. The key is in determining whether the patterns represent signal or noise

I go into every meeting, into every room and for every speech understanding the standard deviation, the Bell Curve. I know there are about 10-15 percent of people in the room, who say, "I've been trying to say this for years. Finally. I agree. Yes, yes, yes." I know there are about 15 percent of the people in the room who think I'm an idiot, who think I don't know what I'm talking about, who think I'm naive or I have oversimplified everything. The majority who are open to the ideal.

They think that intelligence is about noticing things are relevant (detecting patterns); in a complex world, intelligence consists in ignoring things that are irrelevant (avoiding false patterns)

No great marketing decisions have ever been made on qualitative data

Remember, half the people you know are below average.

[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.

Distinguishing the signal from the noise requires both scientific knowledge and self-knowledge: the serenity to accept the things we cannot predict, the courage to predict the things we can, and the wisdom to know the difference.

Of course, analysis can sometimes give more accurate results than intuition but usually it’s just a lot of work. I normally do what my intuition tells me to do. Most of the time spent thinking is just to double-check.

I keep saying the sexy job in the next ten years will be statisticians. People think I'm joking, but who would've guessed that computer engineers would've been the sexy job of the 1990s?