George Monbiot Quotes

One of the distinguishing features of anything that aspires to the name of science is the reproducibility of experimental results.

The best scientific way to discover if one factor influences another is to do a controlled experiment.

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

The scientific method actually correctly uses the most direct evidence as the most reliable, because that's the way you are least likely to get led astray into dead ends and to misunderstand your data.

Scientists learn about the world in three ways: They analyze statistical patterns in the data, they do experiments, and they learn from the data and ideas of other scientists. The recent studies show that children also learn in these ways.

All too often when liberals cite statistics, they forget the statisticians' warning that correlation is not causation.

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.

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.

Scientific method: There's a madness in the method.

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

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.

It is a truism to say that a good experiment is precisely that which spares us the exertion of thinking: the better it is, the less we have to worry about its interpretation, about what it really means.

Every theory presented as a scientific concept is just that; it's a theory that tries to explain more about the world than previous theories have done. It is open to being challenged and to being proven incorrect.

Truth in science can be defined as the working hypothesis best suited to open the way to the next better one.

Much of what I do in my job is think about whether relationships we see in data are causal, as opposed to just reflecting correlations. It's exactly these issues which come up in evaluating studies in public health.

The process of science is difficult and challenging. It involves always being aware that your ideas might be right or they might be wrong. I think it's that kind of balance that makes science so interesting.

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.

Science isn't about authority or white coats; it's about following a method. That method is built on core principles: precision and transparency; being clear about your methods; being honest about your results; and drawing a clear line between the results, on the one hand, and your judgment calls about how those results support a hypothesis.

What intrigues basic scientists like me is that anytime we do a series of experiments, there are going to be three or four new questions that come up when you think you've answered one.

We should teach the students, as well as executives, how to conduct experiments, how to examine data, and how to use these tools to make better decisions.

Most physicists like myself won't believe the result until every possible caveat has been investigated and/or the result is confirmed elsewhere.

I love science. I hate supposition, superstition, exaggeration and falsified data. Show me the research, show me the results, show me the conclusions - and then show me some qualified peer reviews of all that.

It is also a good rule not to put overmuch confidence in the observational results that are put forward until they are confirmed by theory.

True science is never speculative; it employs hypotheses as suggesting points for inquiry, but it never adopts the hypotheses as though they were demonstrated propositions.