Causal relationships are studied by manipulating factors thought to influence the phenomena of interest while controlling other variables relevant to the experimental outcomes.

(Changing slightly the composition of training sets between those dates did not notably affect the experimental outcome.)

A greater difference between hypotheses and conclusions means more new ideas suggested by the experimental outcome, thus a greater progress.

In yesterday's mathematical biology, a model's utility could always be equated with its ability to generate testable predictions about new experimental outcomes.

The result is a logical framework in which each quadrant represents an experimental outcome compared with the mean.

Although this is generally not lethal, the radiation is high enough to affect the immune system and other biological pathways, which may ultimately change experimental outcomes.

(The experimental outcome was statistically significant and adjusted for variables such as non-affective preference for certain characters).

It was supposed that, in every circumstance in which there is a choice of experimental outcome, in fact each possibility is realised.

For statistical correlational analysis to have any chance of succeeding, one needs many more separate experimental outcomes than there are variables to be tested.

It is an experimental outcome which does not show an otherwise expected effect.