John Tukey Quotes

The world is a bell curve. Classroom test scores, employee performance in a company or how many people really, really like you. No matter the population you're studying, they always fit neatly across the standard deviations of the famous bell curve.

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.

A lot of people seem to think that data science is just a process of adding up a bunch of data and looking at the results, but that's actually not at all what the process is.

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 greatest moments are those when you see the result pop up in a graph or in your statistics analysis - that moment you realise you know something no one else does and you get the pleasure of thinking about how to tell them.

The type of measure used placed constraints on which statistics can be used.

The statistics might have a Eurosceptic cast, but they are not exactly a fun read. Few of us want to wade through ONS graphs or European Commission tables.

There is a reasonable concern that posting raw data can be misleading for those who are not trained in its use and who do not have the broader perspective within which to place a particular piece of data that is raw.

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

Definition of a Statistician: A man who believes figures don't lie, but admits than under analysis some of them won't stand up either.

We all know that players will hit a few more home runs than usual in some years and a few less in others. But the mathematics of chance also predicts that some years they'll hit a lot more, and some years a lot less.

Rob Engle and I are concerned with extracting useful implications from economic data, and so the properties of the data are of particular importance.

We have entered an era where the kinds of data and analyses that people run have gotten incredibly complicated. So you have researchers using sophisticated software programs that they probably don't understand but are generally accepted and everyone [in the field] uses.

We must never let a blizzard of statistics blind us to the real lives and people behind them.

It is easy to lie with statistics. It is hard to tell the truth without it.

Being insignificant statistically doesn't mean it's right or wrong. It just means you don't have enough data to show yes or no.

The big mystery of Big Data is causation versus correlation.

If we just focus on stats, we're gonna eventually not have them.

Numbers can't speak for themselves, and data sets - no matter their scale - are still objects of human design.

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.

The median isn't the message.

But the indeterminate future is somehow one in which probability and statistics are the dominant modality for making sense of the world. Bell curves and random walks define what the future is going to look like. The standard pedagogical argument is that high schools should get rid of calculus and replace it with statistics, which is really important and actually useful. There has been a powerful shift toward the idea that statistical ways of thinking are going to drive the future.

Remember, half the people you know are below average.

The next darwin is more likely to be a data wonk than a naturalist wandering through an exotic landscape.

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