Robert Sternberg Quotes

Statistics is, or should be, about scientific investigation and how to do it better, but many statisticians believe it is a branch of mathematics. Now I agree that the physicist, the chemist, the engineer, and the statistician can never know too much mathematics, but their objectives should be better physics, better chemistry, better engineering, and in the case of statistics, better scientific investigation. Whether in any given study this implies more or less mathematics is incidental.

If you're a social scientist worth your salt, you never do a univariate analysis.

An experiment is a question which science poses to Nature and a measurement is the recording of Nature's answer.

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

To call in the statistician after the experiment is done may be no more than asking him to perform a post-mortem examination: he may be able to say what the experiment died of.

To consult the statistician after an experiment is finished is often merely to ask him to conduct a post mortem examination. He can perhaps say what the experiment died of.

Experimental economics is about conducting experiments: bringing economics into the laboratory or creating controlled conditions in the field that allow us to understand better what we are seeing in less controlled circumstances.

There are many things that you can't measure. But the great fun of what I do for a living is figuring out ways to measure things that people previously considered intangible.

At the beginning of all experimental work stands the choice of the appropriate technique of investigation.

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.

Good data is hard to find. Hard data is good to find.

Our polling methodology has gotten outdated, and, in fact, it's not really telling us what it needs to be telling us.

What's nice about experiments is that they are much more closely tied to what theorists think about the world than normal empirical research. You can design your experiment to exactly ask the question you want to ask. This is not true about normal empirical research.

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

We should be cautious about embracing data before it is published in the academic press, and must always avoid treating correlation as causation.

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

... the actual and physical conduct of an experiment must govern the statistical procedure of its interpretation.

Quantitative methods are no more synonymous with objectivity than qualitative methods are synonymous with subjectivity.

The impulse to collect data preceded the ability to make sense of it. People facing a complicated problem measure whatever they can easily measure. But the measurements by themselves don’t lead to understanding.

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.

Statistics are just a compilation of people's stories put on paper, and legislation is our attempt to address those real challenges for people.

When I started in the nineties, a sample size was a 4 and a 6.

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 'data' (given) of research are not so much given as taken out of a constantly elusive matrix of happenings. We should speak of capta rather than data.

If one in twenty does not seem high enough odds, we may, if we prefer it, draw the line at one in fifty (the 2 per cent. point), or one in a hundred (the 1 per cent. point). Personally, the writer prefers to set a low standard of significance at the 5 per cent. point, and ignore entirely all results which fail to reach this level. A scientific fact should be regarded as experimentally established only if a properly designed experiment rarely fails to give this level of significance.