This is typical of the way orthodox methods waste information; in this example we have, in effect, thrown away half of our data whatever the value of...

This is typical of the way orthodox methods waste information; in this example we have, in effect, thrown away half of our data whatever the value of n. Indeed, R. A. Fisher perceived this long ago, remarking that a procedure that loses half the information in the data, wastes half of the work expended in acquiring the data. But modern orthodox practitioners seem never to perceive this, because they continue to fantasize about frequencies, and do not think in terms of information at all. A fantastic example appeared in a work on econometrics (Valavanis, 1959, p. 60) where the author attached such great importance to removing bias that he advocated throwing away not just half the data but practically all them, if necessary, to achieve this. Why do they do this? Why do orthodoxians put such exaggerated emphasis on bias?