Key points are not available for this paper at this time.
SUMMARY An explicit account is given of a procedure for assessing goodness of fit of some observations with a hypothesis, generally known as a “test of significance”; the description is close in spirit to R. A. Fisher’s original conception. The relation of this test procedure with Bayesian procedures and with the Neyman–Pearson theory of tests is discussed. Some very tentative suggestions are made regarding the choice of a test criterion and the use to which the result of the test can be put. The role of conditional sampling distributions is studied. Various examples are discussed. In particular, a brief exploration is made in the apparently virgin territory of testing goodness of fit when the observations have been taken according to a sequential rule.
F. J. Anscombe (Tue,) studied this question.