Ronald Fisher Quotes

If your experiment needs statistics, you ought to have done a better experiment.

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.

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.

Any work of science, no matter what its point of departure, cannot become fully convincing until it crosses the boundary between the theoretical and the experimental: Experimentation must give way to argument, and argument must have recourse to experimentation.

Statistics is a science which ought to be honourable, the basis of many most important sciences; but it is not to be carried on by steam, this science, any more than others are; a wise head is requisite for carrying it on.

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

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.

Statistics is the most important science in the whole world: for upon it depends the practical application of every other science and of every art: the one science essential to all political and social administration, all education, all organization based on experience, for it only gives results of our experience.

[Coining the phrase "test of significance"] Critical tests of this kind may be called tests of significance, and when such tests are available we may discover whether a second sample is or is not significantly different from the first.

The analysis of variance is not a mathematical theorem, but rather a convenient method of arranging the arithmetic.

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

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.

If you're a physicist, for heaven's sake, and here is the experiment, and you have a theory, and the theory doesn't agree with the experiment, then you have to cut out the theory. You were wrong with the theory.

I am frequently astonished that it so often results in correct predictions of experimental results.

Only by observing this condition would the results of our work be regarded as fully conclusive and as having elucidated the normal course of the phenomena.

The value and utility of any experiment are determined by the fitness of the material to the purpose for which it is used, and thus in the case before us it cannot be immaterial what plants are subjected to experiment and in what manner such experiment is conducted.

But there is only one surefire method of proper pattern recognition, and that is science.

These syllables, about 2,300 in number, were mixed together and then drawn out by chance and used to construct series of different lengths, several of which each time formed the material for a test.

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

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

Today's truth is tomorrow's null hypothesis-and next years's error.

if the result confirms the hypothesis, then you've made a measurement. If the result is contrary to the hypothesis, then you've made a discovery.

I would rather not depend on sophisticated statistics to demonstrate behavior. I prefer to design experiments that will produce interocular effects—hit you between the eyes.

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.

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.